function openSample(page) {
   newWindow = window.open('','Sample','top=50,left=50,width=800,height=750,resizable=1,scrollbars=yes');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.location.href=page;
}

function doNothing() {
	return;
}

function showInvisibleMore() {
   var docDivs = document.body.getElementsByTagName("div"); 
   for (n=0; n<=docDivs.length-1; n++) { 
      if ((docDivs[n].className == "invisiblemore") && (docDivs[n].style.display != "block"))  {
	     docDivs[n].style.display = "block"; 
	  }
	  else if (docDivs[n].className == "invisiblemore") docDivs[n].style.display = "none";
   }
   if (morelink.innerHTML == "more") morelink.innerHTML = "less";
   else morelink.innerHTML = "more";
}


var myMovie="";

function setMovie(autoobj) {
   myMovie=document.getElementsByTagName('object');
   if (myMovie[0]) {
	  if (myName.indexOf('code') !=-1) var movieSrc = "images/" + myName + ".swf";
      else var movieSrc=myMovie[0].movie;  
      var movieWidth = myMovie[0].width;
      var movieHeight = myMovie[0].height;
      var movieCode = '<object classid="clsid:D27CDB6E-AE6D-11cf-96B8-444553540000" codebase="http://download.macromedia.com/pub/shockwave/cabs/flash/swflash.cab#version=6,0,29,0" name="Captivate1" width="' + movieWidth + '" height="' + movieHeight + '" id="Captivate1">';
      movieCode += '<param name="movie" value="' + movieSrc + '">';
      movieCode += '<param name="quality" value="high">';
      movieCode += '<param name="menu" value="false">';
      movieCode += '<param name="loop" value="0">';
      movieCode += '<param name="wmode" value="opaque">';
      movieCode += '<embed src="' + movieSrc + '" width="' + movieWidth + '" height="' + movieHeight + '" loop="0" quality="high" pluginspage="http://www.macromedia.com/go/getflashplayer" type="application/x-shockwave-flash" menu="false" name="embed"></embed>';
      movieCode += '</object>';
      myMovie[0].outerHTML = movieCode;
   }
}


<!-- specify lessons and number of pages in each lesson -->
var m103=100;
var m1030=10;
var m104=10;
var m106=10;

<!-- TRANSLATE -->
<!-- specify titles for each lesson -->
var m103title="One-Way Analysis of Variance"; 
//var m1030title="One-Way Analysis of Variance"; 
var m104title="Summary Statistics";
var m106title="Data Exploration";

var alreadyopen;

<!-- developers: don't edit below this line ----------------------------------- -->
<!-- -------------------------------------------------------------------------- -->
<!-- -------------------------------------------------------------------------- -->
<!-- -------------------------------------------------------------------------- -->




var thisWindow = window.location.href;
var myPath = thisWindow.substring(0,thisWindow.lastIndexOf("/"));
var myName = thisWindow.substring(thisWindow.lastIndexOf("/")+1,thisWindow.lastIndexOf("."));
var myModule = myName.substring(myName.lastIndexOf("m"),myName.lastIndexOf("_"));
var moduleTitle = myModule+"title";

<!-- set text for splash titles depending on whether the deliverable is a lesson or course -->
function setLessonTitle() {
alert(moduleTitle.substring(0,1));
   document.write(eval(moduleTitle));
}

<!-- NEW -->

var myAnalysis="";
var myStat="";
if (myName.substring(0,3) == "eg_") myAnalysis = myName.substring(3); 
else myAnalysis = myName;
if      (myAnalysis == "dist_1")    myStat = "Distributions (Charts and Plots)";
else if (myAnalysis == "dist_1a")   myStat = "Distributions (Box Plot)";
else if (myAnalysis == "dist_1b")   myStat = "Distributions (Pie Chart)";
else if (myAnalysis == "dist_1c")   myStat = "Distributions (Bar Chart)";
else if (myAnalysis == "dist_1d")   myStat = "Distributions (Stem and Leaf Plot)";
else if (myAnalysis == "dist_1e")   myStat = "Distributions (Quantiles Plot)";
else if (myAnalysis == "dist_2")    myStat = "Distributions (Descriptive Statistics)";
else if (myAnalysis == "dist_3")    myStat = "Distributions (Tests for Normality)";
else if (myAnalysis == "dist_4")    myStat = "Distributions (Confidence Intervals)";
else if (myAnalysis == "ttest_1")   myStat = "t-Tests (One Sample)";
else if (myAnalysis == "ttest_2")   myStat = "t-Tests (Paired Sample)";
else if (myAnalysis == "ttest_3")   myStat = "t-Tests (Two Sample)";
else if (myAnalysis == "corr_1")    myStat = "Correlation (Graphical Evaluation)";
else if (myAnalysis == "corr_2")    myStat = "Correlation (Pearson Correlation)";
else if (myAnalysis == "corr_3")    myStat = "Correlation (Spearman Correlation)";
else if (myAnalysis == "linreg_1")  myStat = "Linear Regression (Simple)";
else if (myAnalysis == "linreg_2")  myStat = "Linear Regression (Multiple)";
else if (myAnalysis == "linreg_3")  myStat = "Linear Regression (Polynomial)";
else if (myAnalysis == "linreg_4")  myStat = "Linear Regression (Stepwise)";
else if (myAnalysis == "anova_1")   myStat = "Analysis of Variance (One-Way ANOVA)";
else if (myAnalysis == "anova_2")   myStat = "Analysis of Variance (Two-Way ANOVA)";
else if (myAnalysis == "anova_3")   myStat = "Analysis of Variance (Mixed Models)";
else if (myAnalysis == "anova_4")   myStat = "Analysis of Variance (Repeated Measures)";
<!--     else if (myAnalysis == "asso_1") myStat = "Tests of Association (Two-Way Frequency Tables)"; -->
else if (myAnalysis == "asso_1")    myStat = "Tests of Association (Pearson Chi-Square)";
else if (myAnalysis == "asso_2")    myStat = "Tests of Association (Likelihood Ratio Chi-Square)";
else if (myAnalysis == "asso_3")    myStat = "Tests of Association (Mantel-Haenszel Chi-Square)";
else if (myAnalysis == "logreg_1")  myStat = "Logistic Regression (Simple Binary)";
else if (myAnalysis == "logreg_2")  myStat = "Logistic Regression (Multiple Binary)";
else if (myAnalysis == "surv_1")    myStat = "Survival Analysis (Test of Equality over Strata)";
else if (myAnalysis == "surv_2")    myStat = "Survival Analysis (Comparing Survival Functions)";
else if (myAnalysis == "nonpara_1") myStat = "Sign Test (Independent Samples, 1 Sample)";
else if (myAnalysis == "nonpara_2") myStat = "Wilcoxon Signed Rank Test (Independent Samples, 1 Sample)";
else if (myAnalysis == "nonpara_3") myStat = "Median Test (Independent Samples, 2 Sample)";
else if (myAnalysis == "nonpara_4") myStat = "Wilcoxon Rank Sum Test (Independent Samples, 2 Sample)";
else if (myAnalysis == "nonpara_5") myStat = "Kruskal-Wallis Test (Independent Samples, 2 Sample)";
else if (myAnalysis == "nonpara_6") myStat = "Kruskal-Wallis Test (Independent Samples, <em>k</em> Sample)";
else if (myAnalysis == "nonpara_7") myStat = "Wilcoxon Signed Rank Test (Dependent Samples, 2 Sample)";
else if (myAnalysis == "nonpara_8") myStat = "Friedman Test (Dependent Samples, <em>k</em> Sample)";
else if (myAnalysis == "nonpara_9") myStat = "Spearman Correlation";

function writeStat() {
   if (myStat) document.write(myStat);
}

function displayStatProblem(probID) {
alert('display ' + probID + ' only');
}

function showExerciseSolution(spanName) {
   exerciseSolution=document.getElementById(spanName);
   if(exerciseSolution.style.display=='none') exerciseSolution.style.display='block';
   else exerciseSolution.style.display='none';
}

function hideSpans() {
 //     var docSpans = document.body.getElementsByTagName("span"); 
//     for (n=0; n<=docSpans.length-1; n++) { 
 //        if (docSpans[n].className == "child") {
//			 docSpans[n].style.display="none";
//		 }
//	  }
   EX1Child.style.display = "none";
   EX2Child.style.display = "none";
}

function hideDivs() {
      var docDivs = document.body.getElementsByTagName("div"); 
      for (n=0; n<=docDivs.length-1; n++) { 
         if (docDivs[n].className == "child") {
			 docDivs[n].style.display="none";
		 }
	  }
}


function openStatGlossary() {
      var docSpans = document.body.getElementsByTagName("span"); 
      for (n=0; n<=docSpans.length-1; n++) { 
         if (docSpans[n].name == glossaryTerm) {
			 docSpans[n].style.display="block";
		 }
	  }
}

function setIframe(page) {
   document.all.statinfo.src=page;
}

function stretchPage() {
   if (this.parent.document.getElementById("iframetd")) {
      showme=this.parent.document.getElementById("iframetd");
      insideHeight=this.document.body.scrollHeight;
      showme.height=insideHeight;
   }   
}

<!-- end of new EG logic -->
	

////////////// end of version code ///////////////////////////

function openGlossary(docname) {
   newWindow = window.open('','Glossary','top=0,left=0,width=370,height=360,resizable=1,scrollbars=yes');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.location.href=docname;
}

function openContentsIndex() {
   if(newWindow && newWindow.open && !newWindow.closed) newWindow.focus();
   else {
      newWindow = window.open('','ContentsIndex','top=0,left=0,width=550,height=500,resizable=1,scrollbars=yes');
      newWindow.focus(); 
	  var newURL=newWindow.document.URL;
      if (newURL=="about:blank") {
	     newWindow.location.href="conttab.htm";  
	  }
   }
}

function openNotes() {
   notesPage=myName + "a.htm";
   newWindow = window.open('','Notes','top=0,left=0,width=500,height=500,resizable=1,scrollbars=yes');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.location.href=notesPage;
}

function openMenu(page) {
   newWindow = window.open(page,'Menu','top=0,left=0,width=400,height=450,resizable=1,scrollbars=yes');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
}

function openJumpMenu(sasversfile) {
   newWindow = window.open('','SASVersion','top=0,left=0,width=400,height=175,resizable=1,scrollbars=yes');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.location.href=sasversfile;
}

function openStatSim(pageName) {
   if (pageName) {
	   page = pageName;  
   }
   else {
   // otherwise open same-named page + sim
	  page = "eg_" + myName + ".htm";   
   }
   myWidth = screen.availWidth;
///// get rid of /////////////////   
  // var task = document.getElementById('taskDescription');
//   var taskDescHeight = task.scrollHeight;
//   var simObj=document.getElementById("Captivate1");
//   var simWidth = parseInt(simObj.width);
 //  var simHeight = parseInt(simObj.height) + taskDescHeight + 70;
//   newWidth = screen.availWidth;
//   newHeight = simHeight + 60;
 //  window.resizeTo(newWidth,newHeight);
//////////////////////////////////////////////////
   
   if ((pageName) && (pageName.indexOf('code.htm') !=-1)) newWindow = window.open('','ViewCode','top=0,left=0,width=' + myWidth  + ',height=750,resizable=1,scrollbars=yes');
   else newWindow = window.open('','Simulation','top=0,left=0,width=' + myWidth  + ',height=750,resizable=1,scrollbars=yes');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.focus();
   newWindow.location.href=page;
}
   
   
 var simDiv="";
function hideShowSimulation() {
   simObj = document.getElementById('movie');
   divObj = document.getElementById('scroller');
   if (window.location.hash != "#sim") {
      simObj.style.display = "none";
	  divObj.className="";
      resizeStatSim();
//simDiv.style.height = simHeight;
   }
   else {
      simObj.style.display = "block";
	  sizeScrollingDiv();
	  divObj.className="scrollDiv";
	  sizeStatSim();
//	  window.location = myName + ".htm";
   }
}
  
   
   
   
   
   
   
   

function oldopenSimulation() {
   var mySim = myName + "sim.htm";
   newWindow = window.open('','Simulation','top=0,left=0,width=600,height=700,resizable=1,scrollbars=yes');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.location.href=mySim;
}


function OLDopenStatSim(page) {
   var selObj = document.getElementById('openex');
   var selMode = selObj.options[selObj.selectedIndex].value;
   var param;
   if (selMode != "x") {
	   if (selMode == "sim") param = ".htm#sim";
	   else param = "sim.htm";
      openOther(myName + selMode + param);
   }
   else alert('Please select a way to perform the analysis.');  
}

var simDiv="";
function hideShowSimulation() {
   simObj = document.getElementById('movie');
   divObj = document.getElementById('scroller');
   if (window.location.hash != "#sim") {
      simObj.style.display = "none";
	  divObj.className="";
      resizeStatSim();
//simDiv.style.height = simHeight;
   }
   else {
      simObj.style.display = "block";
	  sizeScrollingDiv();
	  divObj.className="scrollDiv";
	  sizeStatSim();
//	  window.location = myName + ".htm";
   }
}

function openSubForm() {
	myForm = "http://support.sas.com/training/elearn/catalog/stat_library/submission_form.html";
   newWindow = window.open(myForm,'Other','top=0,left=0,width=1000,height=750,resizable=1,scrollbars=yes,location=no');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
}


function openOther(page) {
   newWindow = window.open('','Other','top=0,left=0,width=600,height=750,resizable=1,scrollbars=yes');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.location.href=page;
}

function openFlash(movie,wmovie,hmovie) {
   if (movie) codemovie=movie;
   else codemovie=myName + "code.htm";
   if (wmovie) codew=wmovie;
   else codew=750;
   if (hmovie) codeh=hmovie;
   else codeh=770;
   newWindow = window.open('','Flash','top=0,left=0,width='+codew+',height='+codeh+',resizable=0,scrollbars=no');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.location.href=codemovie;
}

function openOther2(page) {
   newWindow = window.open('','Other2','top=25,left=25,width=600,height=750,resizable=1,scrollbars=yes');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.location.href=page;
}

function openOther3(page) {
   newWindow = window.open('','Other3','top=50,left=50,width=600,height=750,resizable=1,scrollbars=yes');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.location.href=page;
}

function openOther4(page) {
   newWindow = window.open('','Other4','top=75,left=75,width=750,height=750,resizable=1,scrollbars=yes');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.location.href=page;
}

function openDoc(page) {
   newWindow = window.open('','Documentation','top=0,left=0,width=640,height=520,resizable=1,scrollbars=yes');
   var newURL=newWindow.document.URL;
   if (newURL=="about:blank") newWindow.location.href=page;
   else {
      newWindow.close();
      openDoc(page);
   }
}

function openLargeToolbar(page) {
   newWindow = window.open('','Information','top=0,left=0,width=850,height=750,resizable=1,scrollbars=yes,toolbar=yes');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.location.href=page;
}


<!-- TRANSLATE -->
<!-- change "<TITLE>Details</TITLE>" and button text "VALUE='Close'" if needed -->
var newWind;
function openImage(img,x,y){ 
   var output; 
   if (newWind != null) newWind.close(); 
   x=eval(x+50);
   y=eval(y+80);
   newWind = window.open("","Details","HEIGHT="+y+",WIDTH="+x+",scrollbars,resizable,top=5,left=5"); 
   output="<HTML><HEAD><TITLE>Details</TITLE></HEAD><BODY BGCOLOR='#FFFFF0' ";  
   output+="onLoad='this.focus()' onBlur='opener.newWind=null'><CENTER>"; 
   output+="<IMG ALT='Full window' SRC='"+img+"'>"; 
   output+="<FORM name='form1'><INPUT TYPE='button' name='Button' VALUE='Close' onClick='self.close()'>"; 
   output+="</FORM></CENTER></BODY></HTML>"; 
   newWind.document.write(output); 
   newWind.document.close(); 
} 

// writes as January 1, 2002
  function GetMonth(intMonth){
<!-- TRANSLATE -->
<!-- change month text if needed -->
    var MonthArray = new Array("January", "February", "March",
                               "April", "May", "June",
                               "July", "August", "September",
                               "October", "November", "December") 
    return MonthArray[intMonth] 	  	 
    }
  function getDateStr(){
    var today = new Date()
    var year = today.getYear()
    if(year<1000) year+=1900
    var todayStr = GetMonth(today.getMonth()) + " " + today.getDate()
    todayStr += ", " + year
    return todayStr
    }

// writes as 1/2/2002	
function DateToday() {
   var Today=new Date();
   var ThisDay=Today.getDate();
   var ThisMonth=Today.getMonth()+1;
   var ThisYear=Today.getFullYear();
   return ThisMonth+"/"+ThisDay+"/"+ThisYear;
}






function showByPosition(object,x,y,e) {
//alert('starting showByPosition');
    var x = 25;
	var y= 0;
	var e=event;

    if (document.layers && document.layers[object]) {
//alert('document.layers');
        if ((e.x + x + 50 + document.layers[object].clip.width) > (window.pageXOffset + window.innerWidth))
            x = x - document.layers[object].clip.width;

        if ((e.y + y + 50 + document.layers[object].clip.height) > (window.pageYOffset + window.innerHeight))
            y *= -4;

        document.layers[object].left = e.x + x;
        document.layers[object].top = e.y + y;
        document.layers[object].visibility = 'visible';
    }
    else if (document.all) {
//alert('document.all');
        e = window.event;
//alert('event is ' + e);

//alert(document.all[object].clientWidth);

        if ((e.x + x + document.all[object].clientWidth) > (document.body.clientWidth + document.body.scrollLeft)) {
            x = (document.body.clientWidth + document.body.scrollLeft) - document.all[object].clientWidth;
//clientWidth: Retrieves the width of the object including padding, but not including margin, border, or scroll bar.		
//scrollLeft: Sets or retrieves the distance between the left edge of the object and the leftmost portion of the content currently visible in the window. 

//alert('x1 is ' + x);
        }
        else {
            x = e.x + x;
//alert('x2 is ' + x);
		}

        if ((e.y + y + document.all[object].clientHeight) > (document.body.clientHeight + document.body.scrollTop)) {
//clientHeight: Retrieves the height of the object including padding, but not including margin, border, or scroll bar. 		
//scrollTop: Sets or retrieves the distance between the top of the object and the topmost portion of the content currently visible in the window. 
//alert('y1 is ' + y);
     //       y = e.y - (y * 4);
	 y = e.y - (y * 4);
//alert('y1 is ' + y);
		}
        else {
//alert(document.body.clientHeight + "   " + document.body.scrollTop);
            y = e.y + y + document.body.scrollTop;
//alert('y2 is ' + y);
		}
//alert('document.all[object].clientHeight=' + document.all[object].clientHeight +"\n" + 'document.body.clientHeight=' + document.body.clientHeight +"\n" + 'document.body.scrollTop=' + document.body.scrollTop +"\n" + 'e.y=' + e.y + "\n" + 'y is ' + y);
//alert('left is ' +document.all[object].style.posLeft);
//alert('top is ' +document.all[object].style.posTop);
//alert('visibility is ' +document.all[object].style.visibility);
//x = e.x + x;
//y = e.y + y;
        document.all[object].style.posLeft = x;
        document.all[object].style.posTop = y;
        document.all[object].style.visibility = 'visible';
    }
}


function hide(object) {
    if (document.layers && document.layers[object])
        document.layers[object].visibility = 'hidden';
    else if (document.all)
        document.all[object].style.visibility = 'hidden';
}

var myBackgroundColor="";
function changeBackground() {
   var myBackgroundColor=this.style.backgroundColor;
   this.style.backgroundColor="#ffff00";
}

function returnBackground() {
   this.style.backgroundColor=myBackgroundColor;
}

function makeAreaGray(object,state) {
// alert(state);
if (state == "on") object.className="normal";
else object.className="transbar";
}

//////////////////// recent for tabs and so on ///////////////////

function showExercises() {
   exer.style.display="block";
   setTabBack('_exer');	
}


var identifier = "";
var goto = "";

function showContent(linkID,tabID) {
//   var goto="";
   <!-- if the call is subject_exer, get identifier from cookie -->
   if ((linkID == "subject") && (tabID == "_exer")) {
	       var _probtab = document.getElementById('_prob');
	      if(_probtab) {
			 _prob.style.display = "none";
			 _data.style.display = "none";
			 _sol.style.display  = "none";
			 document.images.tabstripe.width="350";
		  }
	      <!-- get subject from cookie -->
   	      subject_begin = (document.cookie.indexOf('StatSubject=')+12);
   	      subject_end   = (document.cookie.indexOf(";",subject_begin));
   	      if (subject_end == -1) subject_end = document.cookie.length;
   //	      mySubject = (document.cookie.substring(subject_begin,subject_end));
          <!-- make everything general for the new site -->
   	      mySubject = "general";
		  identifier = "";
		  goto = mySubject + "_";
   }
   <!-- else if another tab, use identifier; if none, give msg -->
   else if (linkID == "subject") {
	   if (identifier) goto = identifier + "_";
	   else {
		   alert('Please select an exercise.');
		   return;
	   }
   }
   <!-- else it's a link -- use linkID -->
   else {
	   goto = linkID + "_";
	   identifier = linkID;
   }
   <!-- display the matching div -->
   var docDivs = document.body.getElementsByTagName("div"); 
   for (n=0; n<=docDivs.length-1; n++) { 
      if ((docDivs[n].id.indexOf(goto) !=-1) && (docDivs[n].id.indexOf(tabID) !=-1)) {
	     docDivs[n].style.display = "block"; 
         if (tabID == "_prob") {
		  	 _prob.style.display = "block";
	  		 _data.style.display = "block";
	  		 _sol.style.display  = "block";
			 document.images.tabstripe.width="50";
		 }
      }
      else if (docDivs[n].className == "invisible") docDivs[n].style.display = "none";
   }
   setTabBack(tabID);
}

function setTabBack(tabID) {
   var docTDs = document.body.getElementsByTagName("td"); 
   for (n=0; n<=docTDs.length-1; n++) { 
      if (docTDs[n].id == tabID) {
	        docTDs[n].style.backgroundImage = "url(navimages/tabup.gif)";
	        docTDs[n].style.fontWeight = "bold";
	  }
	  else if (docTDs[n].className.indexOf("tabback") !=-1) {
	     docTDs[n].style.backgroundImage = "url(navimages/tabdown.gif)";
	     docTDs[n].style.fontWeight = "normal";
	  }
   }
}

function printExercise() {
	var exercise = "";
   <!-- display the matching div -->
   var docDivs = document.body.getElementsByTagName("div"); 
   for (n=0; n<=docDivs.length-1; n++) { 
      if (docDivs[n].id.indexOf(goto) !=-1) {
	     exercise+=docDivs[n].innerHTML;
//	     exercise+="<p>" + docDivs[n].innerHTML + "</p>";
	  }
   }
   <!-- open window with content -->
   newWind = window.open("","PrintEx","HEIGHT=500,WIDTH=700,scrollbars,resizable,top=5,left=5"); 
   extext='<HTML><HEAD><TITLE>Printer Friendly Version of Exercise</TITLE>';  
   extext+='<SCRIPT LANGUAGE="JavaScript" SRC="tut.js"></SCRIPT>';  
   extext+='<link rel="stylesheet" href="tut.css"></HEAD><BODY BGCOLOR="#FFFFF0" ';  
   extext+='onLoad="this.focus()" onBlur="opener.newWind=null">'; 
 //  extext+='<font color="#003399"><strong>Print Version of ' + goto + '</strong></font>';
   extext+='<div nowrap><img src="navimages/print.gif" alt="Print Exercise" width="16" height="16">';
   extext+='&nbsp;<a href="JavaScript: self.print();"><font size="1">Print This Exercise</font></a></div>';
   extext+='<hr size="1" color="#003399">';    
   extext+='<table width="95%" border="0" cellspacing="0" cellpadding="5" align="center">';
   extext+='  <tr valign="top">';
   extext+='    <td>' + exercise +'</td>';
   extext+='  </tr>';
   extext+='</table>';
   extext+='<hr size="1" color="#003399">';    
   extext+='<CENTER><FORM name="form1">';
   extext+='&nbsp;&nbsp;&nbsp;<INPUT TYPE="button" name="Close" VALUE="Close" onClick="self.close()">'; 
   extext+='</FORM></CENTER>'; 
   extext+='</BODY></HTML>'; 
   newWind.document.write(extext); 
   newWind.printimg.style.display = "none"; 
   newWind.downldimg.style.display = "none"; 
   newWind.document.close(); 
 //  newWind.print();
}

function SIMopenSimSteps() {
   var simSteps="";
   var tasktitle="";
   if (opener) var simDivs = opener.document.getElementsByTagName("div"); 
   else var simDivs = document.getElementsByTagName("div"); 
   for (n=0; n<=simDivs.length-1; n++) {  
      var divClass=simDivs[n].className;
      if (divClass.indexOf('stepText') != -1){
	     simSteps+="<p>" + simDivs[n].innerHTML + "</p>";
	  }
   }
   if (opener) tasktitle = opener.document.getElementById('taskDescription').innerText + "<p>";
   else tasktitle = document.getElementById('taskDescription').innerText + "<p>";

   newWind = window.open("","TextSteps","HEIGHT=500,WIDTH=500,scrollbars,resizable,top=5,left=5"); 
   if (self.name == "Simulation") textsim='<HTML><HEAD><TITLE>Solution to Practice Simulation</TITLE>';  
   else textsim='<HTML><HEAD><TITLE>Text-Only Version of Steps</TITLE>';  
   textsim+='<SCRIPT LANGUAGE="JavaScript" SRC="../tut.js"></SCRIPT>';  
   textsim+='<link rel="stylesheet" href="../tut.css"></HEAD><BODY BGCOLOR="#FFFFF0" ';  
   textsim+='onLoad="this.focus()" onBlur="opener.newWind=null">'; 
   textsim+='<font color="#003399"><strong>' + tasktitle + '</strong></font>';
   textsim+='<table width="95%" border="0" cellspacing="0" cellpadding="5" align="center">';
   textsim+='  <tr>';
   textsim+='    <td>' + simSteps +'</td>';
   textsim+='  </tr>';
   textsim+='</table>';
   textsim+='<CENTER><FORM name="form1"><INPUT TYPE="button" name="Button" VALUE="Close" onClick="self.close()">'; 
   textsim+='</FORM></CENTER></BODY></HTML>'; 
   newWind.document.write(textsim); 
   newWind.document.close(); 
}


function OLDshowContent(linkID) {
   identifier = "bus"; //would actually get the domain from the cookie
   if(identifier) {
      var docDivs = document.body.getElementsByTagName("div"); 
      for (n=0; n<=docDivs.length-1; n++) { 
 //        if (docDivs[n].id.indexOf(linkID) !=-1) {
         if ((docDivs[n].id.indexOf(identifier) !=-1) && (docDivs[n].id.indexOf(linkID) !=-1)) {
	        docDivs[n].style.display = "block"; 
	     }
	     else if (docDivs[n].className == "invisible") docDivs[n].style.display = "none";
      }
      setTabBack(linkID);
   }
 //  }
 //  else alert('Please select an exercise.');
}


function RECENTshowContent(linkID) {
 //  if((identifier) || (myName.substring(0,3) == "eg_")) {
      var docDivs = document.body.getElementsByTagName("div"); 
      for (n=0; n<=docDivs.length-1; n++) { 
         divID = linkID;
         if (docDivs[n].id.indexOf(divID)!= -1) {
	        docDivs[n].style.display = "block";
	     }
	     else if (docDivs[n].className == "invisible") docDivs[n].style.display = "none";
      }
      setTabBack(linkID);
 //  }
 //  else alert('Please select an exercise.');
}

function OLDshowContent(tabID) {
   var docDivs = document.body.getElementsByTagName("div"); 
   for (n=0; n<=docDivs.length-1; n++) { 
      divID = tabID + "_content";
      if (docDivs[n].id.indexOf(divID)!= -1) {
	     docDivs[n].style.display = "block";
	  }
	  else if (docDivs[n].className == "invisible") docDivs[n].style.display = "none";
   }
   setTabBack(tabID);
}



function showTab(thistab) {
	//	 alert('showtab');
   tabID = thistab;
   setTabBack(tabID);
//   showContent(tabID);
}

function REVISEDsetTabBack(tabID) {
   var docTDs = document.body.getElementsByTagName("td"); 
   for (n=0; n<=docTDs.length-1; n++) { 
      if (docTDs[n].id == tabID) {
         if (docTDs[n].className == "tabeg") {
		    docTDs[n].style.fontWeight = "bold";
		 }
         else if (docTDs[n].className == "tabback") {
	        docTDs[n].className = "tabselect";
		    docTDs[n].style.fontWeight = "bold";
		 }
      }
	  else if (docTDs[n].className == "tabselect") {
	     docTDs[n].className = "tabback";
		 docTDs[n].style.fontWeight = "normal";
	  }
	  else if (docTDs[n].className == "tabeg") {
		 docTDs[n].style.fontWeight = "normal";
	  }
   }
}

function OLDREVISEDsetTabBack(tabID) {
   var docTDs = document.body.getElementsByTagName("td"); 
   for (n=0; n<=docTDs.length-1; n++) { 
      if (docTDs[n].id == tabID) {
	     docTDs[n].className = "tabselect";
		 docTDs[n].style.fontWeight = "bold";
      }
	  else if (docTDs[n].className == "tabselect") {
	     docTDs[n].className = "tabback";
		 docTDs[n].style.fontWeight = "normal";
      }
   }
}



function OLDwriteFirstObject(objectID) {
	
//	document.exercises.style.display="block";
	
   if (objectID) {
      thisTab = objectID;
	  thisObject = objectID + "_content";
   }
   else {
	  thisTab = "ega";
      thisObject = "ega_content";
   }
   firstObj = document.getElementById(thisObject);
   firstObj.style.display = "block";
   firstTab = document.getElementById(thisTab);
   firstTab.style.fontWeight = "bold";
}

function writeParentTitle() {
   var docTDs = document.body.getElementsByTagName("td"); 
   for (n=0; n<=docTDs.length-1; n++) { 
      if (docTDs[n].className == "sectionTitle") {
	     var myParentID = docTDs[n].parentNode.parentNode.parentNode.id; //link1x_content
		 if (myParentID) {
		 var linkRef = myParentID.substring(0,5);
         var linkTitle = document.getElementById(linkRef).innerText;
		 docTDs[n].innerHTML = '<font color="#003399"><strong>' + linkTitle + '</strong></font>';
         }
	  }
   }
}

function downloadSampData(dsname) {
   newWindow = window.open('xData.htm#' + dsname,'ChooseData','top=0,left=500,width=300,height=135,resizable=1,scrollbars=auto');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.focus();
}


function listData(domain,datatype) {
	var myds = document.getElementById('dslist');
	var myDslist = '<br><font class="largegray" size="+2">Available data sets:</font><br><br><em><font color="#656565">To save a data set, right-click the data set name and select <strong>Save Target As</strong>. <br>You can save individual data sets or a zip file of all data sets for a subject area.</font></em><br><br>';
	if ((domain=="x") || (datatype=="x")) alert('Please select both a subject and format.');
    else {
	   for (var i=0; i<dataSets.length; i++) {	
	      if (((domain == "all") || (dataSets[i][0] == domain)) && (dataSets[i][1] == datatype)) {
		     myDslist += '<a target="_blank" href="data/' + dataSets[i][3] + '" class="tlink">' + dataSets[i][2] + '</a><br>' + dataSets[i][4] + '<br><br>';
		  }
	   }
	   myds.innerHTML = myDslist;
	}
}

function openData(type) {
	if (type=="zip") {
	   var selObj = document.getElementById('pickdata');
	   var myDsname = selObj.options[selObj.selectedIndex].value;
	   var myData = myPath + "/data/" + myDsname + "." + type;
       zipWindow = window.open(myData,'ZipFile','width=100,height=100,resizable=0,scrollbars=no');
	}
	else {
	   var myDsname = document.location.hash.substring(1);
	   var myData = myPath + "/data/" + myDsname + "." + type;
	   document.location.href = myData;
	}
}


function hideTitle() {
 //  parent.frames.tabs.titleT.style.display = 'none';
 
 
//   if (parent.frames.content.location.href.indexOf("splash.htm") == -1) {
//alert('not splash');
 //     parent.frames.tabs.titleText.style.display = 'none';
//   }
//   else parent.frames.tabs.titleText.style.display = 'inline';
//if (document.location.href.indexOf("splash.htm") == -1) parent.frames.tabs.titleText.style.display = 'inline';
}

function showTitle() {
//alert('hi');
   parent.frames.tabs.titleT.style.display = 'inline';
}

function showNav(clicktab) {
   parent.frames.nav.location.href = clicktab;
   if (clicktab == "nav.htm") parent.frames.content.location.href = "splash.htm";
   else if (clicktab == "navsas.htm") parent.frames.content.location.href = "splashsas.htm";
}

<!-- bottom navigation and copyright table -->
//var nav_regular_bottom="";
//nav_regular_bottom+='<table width="100%" cellspacing="0" cellpadding="0">';
//nav_regular_bottom+='  <tr>';
//nav_regular_bottom+='    <td width="14"><img src="../navimages/linebox.gif" width="14" height="7" alt=" "></td><td colspan="2"><img src="../navimages/linegray.gif" width="100%" height="7" alt=" "></td></tr>';
//nav_regular_bottom+='  <tr>';
//nav_regular_bottom+='    <td>&nbsp;</td><td valign="top"> <font size="1" color="gray" face="Verdana, Arial, Helvetica, Sans Serif"><a class="copyrightlink" href="JavaScript: openOther(\'../copyrite.htm\')"><font face="Arial, Helvetica, sans-serif">Copyright</font></a><font face="Arial, Helvetica, sans-serif">&copy; 2005 SAS Institute Inc., Cary, NC, USA. All rights reserved.</font></font> <font face="Arial, Helvetica, sans-serif"><br><font size="1" color="gray"><a class="copyrightlink" href="http://www.sas.com/Copyright.html" target="_blank">Terms of Use &amp; Legal Information</a> | <a class="copyrightlink" href="http://www.sas.com/Privacy.html" target="_blank">Privacy Statement</a></font></font></td><td width="60"></td></tr>';

//function writeNav_regular_bottom() {
//   document.write(nav_regular_bottom);
//}

var myWidth;
var myHeight;
var myLeft;
var myTop;
var myChrome;


function openSim() {
   screenWidth = screen.availWidth; 
   screenHeight = screen.availHeight;
   simPage=myName + "sim.htm";
   newWindow = window.open('','Simulation','top=0,left=0,width=800,height=600,resizable=1,scrollbars=yes');
      if (alreadyopen) {
         alreadyopen = false;
      }
   alreadyopen = true;
   newWindow.location.href=simPage;
   newWindow.resizeTo(screenWidth,screenHeight);
}

//var closeButton="";
//closeButton+='<form name="close" method="post" action=""><input type="button" name="Button" value="Close" onClick="JavaScript: self.close()"></form>';

//function writecloseButton() {
//   document.write(closeButton);
//}


//if(document.images){
//downloadn=new Image();downloadn.src="navimages/download.gif";
//downloady=new Image();downloady.src="navimages/download_h.gif";
//}

function rOver(boxL){
   if(document.images)
      {document[boxL].src=eval(boxL+'y.src');}
}

function rOut(boxL){
   if(document.images)
      {document[boxL].src=eval(boxL+'n.src');}
}

/////////// new //////////////////////////

function openKB() {
	if((document.location.hash) && (document.location.href.indexOf('_') !=-1)) {
	//	alert(document.location.hash.substring(1));
		 chgimg("plus" + document.location.hash.substring(1));
		 expandIt(document.location.hash.substring(1)); 
	//	expandIt('KB5'); alert('KB5');
		//KB5A.focus(); KB5A.click();
	}
}

/////////////////////////////// cookie code /////////////////////////

var exp=new Date();exp.setTime(exp.getTime()+(365*86400000));

function setInitialCookie() {
   if(document.cookie) {
	   getSubject();
   }
   else {
      document.cookie = "StatLib=YES;path=/;expires="+exp.toGMTString();
//alert('initial cookie set');
   }
}

function setSubjectCookie(subject) {
   document.cookie = 'StatSubject='+subject+';path=/;expires='+exp.toGMTString();
//alert(document.cookie);
}

function setSubject(domain) {
	var mydomain = domain;
	if (myName == "top_data") {
	   if (mydomain == "biotechnology") {
		  // if (document.images.subjsplash) document.images.exsplash.src = "navimages/spl_bus.gif";
		   pickdomain.options.selectedIndex = 0;
	   }
	   else if (mydomain == "business") {
		//   if (document.images.subjsplash) document.images.exsplash.src = "navimages/spl_hea.gif";
		   pickdomain.options.selectedIndex = 1;
	   }
	   else if (mydomain == "data management") {
		//   if (document.images.subjsplash) document.images.exsplash.src = "navimages/spl_soc.gif";
		   pickdomain.options.selectedIndex = 2;
	   }
	   else if (mydomain == "life science") {
		//   if (document.images.subjsplash) document.images.exsplash.src = "navimages/spl_gen.gif";
		   pickdomain.options.selectedIndex = 3;
	   }
	   else if (mydomain == "statistics") {
		//   if (document.images.subjsplash) document.images.exsplash.src = "navimages/spl_gen.gif";
		   pickdomain.options.selectedIndex = 4;
	   }
	   else if (mydomain == "general") {
		//   if (document.images.subjsplash) document.images.exsplash.src = "navimages/spl_gen.gif";
		   pickdomain.options.selectedIndex = 5;
	   }
	   else {
	//	   if (document.images.subjsplash) document.images.exsplash.src = "navimages/spl_gen.gif";
		   pickdomain.options.selectedIndex = 6;
	   }
	//	   if (document.images.subjsplash) document.images.exsplash.alt = mydomain;
//alert(mydomain);
	   setSubjectCookie(mydomain); 
	}
	// add code here to change small graphic on exercise pages
	else if (myName.indexOf('_') !=-1) {
	   if (mydomain == "business") {
		   if (document.images.subjsplash) document.images.subjsplash.src = "navimages/tab_bus.gif";
		   pickdomain.options.selectedIndex = 0;
	   }
	   else if (mydomain == "health") {
		   if (document.images.subjsplash) document.images.subjsplash.src = "navimages/tab_hea.gif";
		   pickdomain.options.selectedIndex = 1;
	   }
	   else if (mydomain == "social") {
		   if (document.images.subjsplash) document.images.subjsplash.src = "navimages/tab_soc.gif";
		   pickdomain.options.selectedIndex = 2;
	   }
	   else if (mydomain == "general") {
		   if (document.images.subjsplash) document.images.subjsplash.src = "navimages/tab_gen.gif";
		   pickdomain.options.selectedIndex = 3;
	   }
	   else {
		   if (document.images.subjsplash) document.images.subjsplash.src = "navimages/tab_gen.gif";
		   pickdomain.options.selectedIndex = 3;
	   }
	   if (document.images.subjsplash) document.images.subjsplash.alt = mydomain;
	   setSubjectCookie(mydomain);
	   showContent('subject','_exer');
	}
}

var mySubject = "";

function getSubject() {
    if(document.cookie) {
       StatSubject = document.cookie.indexOf('StatSubject=');
       if (StatSubject == -1) {
		   setSubjectCookie('general');
		   setSubject('general');
	   }
	   else {
   	      <!-- get subject from cookie -->
   	      subject_begin = (document.cookie.indexOf('StatSubject=')+12);
   	      subject_end   = (document.cookie.indexOf(";",subject_begin));
   	      if (subject_end == -1) subject_end = document.cookie.length;
   	      mySubject = (document.cookie.substring(subject_begin,subject_end)); 
		//  alert(mySubject);
   	      <!-- set page images based on subject -->
		  setSubject(mySubject);  
	   }
    }
    else {
	   setInitialCookie();
	   getSubject();
	}
	alert(mySubject);
}



function testSelect2() {
   alert('This selection would allow users to download all   \ndata sets in the specified format. Individual data sets are    \navailable from each practice.');
}


function subsetBySubject() {
   if (myName.substring('_') != -1) {
						
						
   }
}

function fillForm() {
	alert('here');
document.form1.email.value="michelle.cueva@sas.com";	
document.form1.name.value="Michelle Cueva";
document.form1.company.value="SAS Institute";
document.form1.domain.value="health";
document.form1.analysis.value="anova_1";
document.form1.dsname.value="MyDataSet";
document.form1.format.value="sas7bdat";
document.form1.dsrows.value=2;
document.form1.dscols.value=2;
document.form1.introdata.value="introdata";
document.form1.sourcedata.value="sourcedata";
document.form1.shorttitle.value="short title";
document.form1.linkdesc.value="link description";
document.form1.studytype.value="nonexp";
document.form1.problem.value="It's a problem, isn't it?";
document.form1.solution.value="There's a solution.";
document.form1.dictionary.value="test";
document.form1.status.value="new";
}


plusn=new Image();plusn.src="navimages/minusblue.gif";
plusy=new Image();plusy.src="navimages/plusblue.gif";
learnhown=new Image();learnhown.src="navimages/learnhow.gif";
learnhowy=new Image();learnhowy.src="navimages/learnhow_h.gif";

function showSteps() {
   newWind = window.open("","TextSteps","HEIGHT=500,WIDTH=500,scrollbars,resizable,top=5,left=5"); 
   textsim='<HTML><HEAD><TITLE>Simulation Steps</TITLE>';  
   textsim+='<link rel="stylesheet" href="tut.css"></HEAD><BODY BGCOLOR="#FFFFF0" ';  
   textsim+='onLoad="this.focus()" onBlur="opener.newWind=null">'; 
   textsim+='<table width="95%" border="0" cellspacing="0" cellpadding="5" align="center">';
   textsim+='  <tr>';
   textsim+='    <td><strong>' + myName + '</strong><br><br>' + scroller.innerHTML +'</td>';
   textsim+='  </tr>';
   textsim+='</table>';
   textsim+='<CENTER><FORM name="form1"><INPUT TYPE="button" name="Button" VALUE="Close" onClick="self.close()">'; 
   textsim+='</FORM></CENTER></BODY></HTML>'; 
   newWind.document.write(textsim); 
   newWind.document.close(); 
   newWind.print();
   newWind.close();
}

function savePage() {
//	controls.style.display = "none";
	document.execCommand("SaveAs","true","questions.htm");
}

// Downloadable data sets by subject area -->
var dataSets=new Array();
// zip files
dataSets[0]=new Array("business","sas7bdat","All Business Data Sets (SAS)","bus_sas.zip","A zip file containing all data sets in SAS format for the Business subject area.");
dataSets[1]=new Array("business","xls","All Business Data Sets (Excel)","bus_xls.zip","A zip file containing all data sets in Excel format for the Business subject area.");
dataSets[2]=new Array("health","sas7bdat","All Health Data Sets (SAS)","hea_sas.zip","A zip file containing all data sets in SAS format for the Health subject area.");
dataSets[3]=new Array("health","xls","All Health Data Sets (Excel)","hea_xls.zip","A zip file containing all data sets in Excel format for the Health subject area.");
dataSets[4]=new Array("social","sas7bdat","All Social Sciences Data Sets (SAS)","soc_sas.zip","A zip file containing all data sets in SAS format for the Social Sciences subject area.");
dataSets[5]=new Array("social","xls","All Social Sciences Data Sets (Excel)","soc_xls.zip","A zip file containing all data sets in Excel format for the Social Sciences subject area.");
dataSets[6]=new Array("general","sas7bdat","All General Data Sets (SAS)","gen_sas.zip","A zip file containing all data sets in SAS format for the General subject area.");
dataSets[7]=new Array("general","xls","All General Data Sets (Excel)","gen_xls.zip","A zip file containing all data sets in Excel format for the General subject area.");
// individual files
dataSets[8]=new Array("general","sas7bdat","Concrete (SAS)","Concrete.sas7bdat","Data about brands of concrete.");
dataSets[9]=new Array("general","xls","Concrete (Excel)","Concrete.xls","Data about brands of concrete.");
dataSets[10]=new Array("health","sas7bdat","Analgesics (SAS)","Analgesics.sas7bdat","Data about analgesics.");
dataSets[11]=new Array("health","xls","Analgesics (Excel)","Analgesics.xls","Data about analgesics.");
dataSets[12]=new Array("social","sas7bdat","MyDataSet (SAS)","MyDataSet.sas7bdat","My social data set.");
dataSets[13]=new Array("social","xls","MyDataSet (Excel)","MyDataSet.xls","My social data set.");
dataSets[14]=new Array("business","sas7bdat","MyDataSet2 (SAS)","MyDataSet2.sas7bdat","My business data set.");
dataSets[15]=new Array("business","xls","MyDataSet2 (Excel)","MyDataSet2.xls","My business data set.");


function listDSNew(domain) {
//	alert('domain=' + domain);
	var numsets=0;
	var myds = document.getElementById('dslist');
	var myDslist='<br><font class="largegray" size="+1">Data sets for your subject:<span id="num">X</span></font><br><br><em><font color="#656565">To save a data set, right-click the data set name and select <strong>Save Target As</strong>. <br>You can save individual data sets or a zip file of all data sets for a subject area.</font></em><br><br><table cellpadding="5" cellspacing="0" style="border:1px solid #ebd7ae;"><tr bgcolor="#fceed1"><td nowrap="nowrap"><strong>Data Set</strong></td><td nowrap="nowrap"><strong>Subject Area</strong></td><td><strong>Statistics</strong></td><td><strong>Size</strong></td></tr>';

	if (domain=="x") alert('Please select a subject.'); 
    else {
	   for (var i=0; i<dataSetsNEW.length; i++) {	
	      if ((domain == "all") || (dataSetsNEW[i][0].toLowerCase().indexOf(domain) != -1)) {
		   myDslist += '<tr valign="top" bgcolor="#FFFFFF"><td><a target="_blank" href="data/' + dataSetsNEW[i][3] + '" class="tlink">' + dataSetsNEW[i][2] + '</a><br>' + dataSetsNEW[i][4].substring(0,150) + '... <span id="DS' + i + 'Parent"><a id="morelinkDS' + i + '" class="morelink" href="JavaScript: return false;" onClick="expandIt(\'DS' + i + '\'); return false;">more</a>...</span><div class="child" id="DS' + i + 'Child"><p><strong>Full Description: </strong>' + dataSetsNEW[i][4] + '<font color="#003399"> ' + dataSetsNEW[i][5] + '</font></p><p><strong>Source: </strong>' + dataSetsNEW[i][6] + '</p></div></td><td>' + dataSetsNEW[i][0] + '</td><td>' + dataSetsNEW[i][7] + '</td><td nowrap="nowrap">' + dataSetsNEW[i][8] + '</td></tr>';
		  numsets++;
		  }
	   }
	   myDslist+='</table>';
	   myds.innerHTML = myDslist;
	   var mynum = document.getElementById('num'); 
	   mynum.innerHTML = "&nbsp;&nbsp;" + numsets;
	   hideDivs();
	}
}

function OLDlistDSNew(domain,datatype) {
	datatype="sas7bdat";
	var numsets=0;
	var myds = document.getElementById('dslist');
		   myDslist += '<tr valign="top" bgcolor="#FFFFFF"><td><a target="_blank" href="data/' + dataSetsNEW[i][3] + '" class="tlink">' + dataSetsNEW[i][2] + '</a><br>' + dataSetsNEW[i][4].substring(0,150) + '... <span id="DS' + i + 'Parent"><a id="morelinkDS' + i + '" class="morelink" href="JavaScript: return false;" onClick="expandIt(\'DS' + i + '\'); return false;">more</a>...</span><div class="child" id="DS' + i + 'Child"><p><strong>Full Description: </strong>' + dataSetsNEW[i][4] + '<font color="#003399"> ' + dataSetsNEW[i][5] + '</font></p><p><strong>Source: </strong>' + dataSetsNEW[i][6] + '</p></div></td><td>' + dataSetsNEW[i][0] + '</td><td>' + dataSetsNEW[i][7] + '</td><td nowrap="nowrap">' + dataSetsNEW[i][8] + '</td></tr>';

	if ((domain=="x") || (datatype=="x")) alert('Please select both a subject and format.'); 
    else {
	   for (var i=0; i<dataSetsNEW.length; i++) {	
	      if (((domain == "all") || (dataSetsNEW[i][0] == domain)) && (dataSetsNEW[i][1] == datatype)) {
		   myDslist += '<tr valign="top" bgcolor="#FFFFFF"><td><a target="_blank" href="data/' + dataSetsNEW[i][3] + '" class="tlink">' + dataSetsNEW[i][2] + '</a><br>' + dataSetsNEW[i][4].substring(0,150) + '... <span id="DS' + i + 'Parent"><a id="morelinkDS' + i + '" class="morelink" href="JavaScript: return false;" onClick="expandIt(\'DS' + i + '\'); return false;">more</a>...</span><div class="child" id="DS' + i + 'Child"><p><strong>Full Description: </strong>' + dataSetsNEW[i][4] + '<font color="#003399"> ' + dataSetsNEW[i][5] + '</font></p><p><strong>Source: </strong>' + dataSetsNEW[i][6] + '</p></div></td><td>' + dataSetsNEW[i][0] + '</td><td>' + dataSetsNEW[i][7] + '</td><td nowrap="nowrap">' + dataSetsNEW[i][8] + '</td></tr>';
		  }
		  numsets++;
	   }
	   myDslist+='</table>' + numsets;
	   myds.innerHTML = myDslist;
	   hideDivs();
	}
}


function FORMERlistData(domain,datatype) {
	var myds = document.getElementById('dslist');
	var myDslist = '<br><font class="largegray" size="+2">Available data sets:</font><br><br><em><font color="#656565">To save a data set, right-click the data set name and select <strong>Save Target As</strong>. <br>You can save individual data sets or a zip file of all data sets for a subject area.</font></em><br><br>';
	if ((domain=="x") || (datatype=="x")) alert('Please select both a subject and format.');
    else {
	   for (var i=0; i<dataSets.length; i++) {	
	      if (((domain == "all") || (dataSets[i][0].toLowercase() == domain)) && (dataSets[i][1] == datatype)) {
		     myDslist += '<a target="_blank" href="data/' + dataSets[i][3] + '" class="tlink">' + dataSets[i][2] + '</a><br>' + dataSets[i][4] + '<br><br>';
		  }
	   }
	   myds.innerHTML = myDslist;
	}
}

var dataSetsNEW=new Array();
dataSetsNEW[0]=new Array("Statistics, General","sas7bdat","A","a.sas7bdat","A clinical trial was conducted comparing two treatments, an experimental drug versus a control. The study was conducted at eight clinics. At each clinic, patients were assigned at random to either the experimental drug or the control. The variables in the data set are the clinic number (CLINIC), the assignment to the experimental drug or the control (TRT), the number of patients with favorable responses (FAV), the number of patients with unfavorable responses (UNFAV), and the total number of patients at that clinic assigned to that treatment (NIJ).","16 rows, 5 columns.","SAS Institute Inc.","Regression, ANOVA, Graphic Analysis","5 KB");
dataSetsNEW[1]=new Array("Statistics, General","sas7bdat","AML Survival","aml_survival.sas7bdat","The dataset AML_Survival Data contains information on a trial conducted by Embury et al. (1977) at Stanford University. The investigators were concerned with the efficacy of maintenance therapy for acute myelogenous leukemia (aml). Initially, patients were treated by chemotherapy until remission. Then, these patients were randomized into two groups-a treatment group that received maintenance therapy and a control group that did not. Individuals in both groups were followed until they suffered a relapse, the event of interest. The event time variable is defined as the length of time in remission, i.e., the time from entry into the study until relapse.","23. rows, 3 columns.","SAS Institute Inc.","Survival","5 KB");
dataSetsNEW[2]=new Array("Statistics, General","sas7bdat","Arrest Rates","arrestrates.sas7bdat","The data set is a record of the arrests per 100,000 people in each age group in the United States from 1970 through 1999. The variables in the data set are: year (YEAR), arrests per 100 thousand in population (RATE), and the age group (AGEGROUP). The age groups are defined as (1) 14 and under, (2) 15-17, (3) 18-20, (4) 21-24, and (5) 25 or over. <br>This data set is a subset of the data in the data set totarrests. <br>The data set could be used to generate descriptive statistics by age group or to do a time series analysis to predict the arrest rates by age group. These predictions might be used in assessing the need for judicial system infrastructure changes. Finally, the data could be used to compare age groups with an ANOVA. <br>","150 rows, 3 columns.","SAS Institute Inc.","Descriptive Statistics, Graphic Analysis, Time Series","9 KB");
dataSetsNEW[3]=new Array("General","sas7bdat","Auction","auction.sas7bdat","This is data from 19 livestock auction markets. The columns include: the number of head of different livestock sold (in thousands) including CATTLE, CALVES, HOGS, and SHEEP, the cost of operation of the auction market (in thousands of dollars) (COST), and the market identifier (MARKETID). The object is to use multiple linear regression to describe the relationship between the cost of operations to the number of livestock sold in the various classes. COST will be the dependent variable and CATTLE, CALVES, HOGS, and SHEEP the independent variables. <p>An additional variable, VOLUME, is the total of all major livestock sold in each market. It is the sum of the variables CATTLE, CALVES, HOGS, and SHEEP, and can be used to demostrate an exact linear dependency between independent variables.","  rows,   columns.","SAS Institute Inc.","Regression, Graphic Analysis","9 KB");
dataSetsNEW[4]=new Array("Statistics, General","sas7bdat","Beer Sales","beer_sales.sas7bdat","Beer sales records monthly sales of beer in hectoliters, along with the average high and low temperatures in the region, over a period of five years. The object is to see how beer sales change over time. You can also consider the relationships between beer sales and temperatures.","4 rows, 60 columns.","SAS Institute Inc.","Regression, Time Series","5 KB");
dataSetsNEW[5]=new Array("General","sas7bdat","Blood Pressure","bloodpressure.sas7bdat","Consider an experiment to examine the effectiveness of a medication in reducing blood pressure. A random sample of individuals with high blood pressure is taken and their diastolic pressure is recorded. The individuals are then placed on medication and one month later their diastolic blood pressure is once again recorded. The dataset contains the following variables: subject, age, baseline blood pressure, and new blood pressure.","60 rows, 4 columns.","SAS Institute Inc.","Paired-Sample T-Test; One-Sample T-Test; Regression, Graphic Analysis","5 KB");
dataSetsNEW[6]=new Array("General","sas7bdat","Boston Housing Data","bostonhousing.sas7bdat","The data set contains census information for 506 housing tracts in the Boston area. You can perform a two-sample t-test to examine the median values of owner-occupied homes in two groups of housing tracts, those near the Charles River and those farther away from it. The data can also be used to develop a regression model to predict median home values based on the other variables in the data set, such as crime rate, the percentage of industrial business acres, nitrogen oxide concentration, the average number of rooms in a home, the percentage of home built before 1940, the accessibility to radial highways, the property tax rate, the percentage of lower economic status families in the housing tract, and the pupil/teacher ratios in the local school.","506 rows, 13 columns.","SAS Institute Inc.","Regression, T-Tests, Graphic Analysis","61 KB");
dataSetsNEW[7]=new Array("Statistics, General","sas7bdat","Calves","calves.sas7bdat","Two types of feed rations (FEED) are given to calves from three different sires (SIRE). The dependent variable is the coded amount of weight gain for each calf (WEIGHTGAIN).","18 rows, 3 columns.","SAS Institute Inc.","ANOVA, Graphic Analysis","9 KB");
dataSetsNEW[8]=new Array("Statistics, General","sas7bdat","Calves2","calves2.sas7bdat","Two types of feed rations (FEED) are given to calves from three different sires (SIRE). The dependent variable is the coded amount of weight gain for each calf (WEIGHTGAIN). (Note: this is the same data as the calves data set but with an empty cell)","18 rows, 3 columns.","SAS Institute Inc.","ANOVA, Graphic Analysis","5 KB");
dataSetsNEW[9]=new Array("Statistics, General","sas7bdat","Candy","candy.sas7bdat","Since 1994, the United States Food and Drug Administration (FDA) has required uniform, easy-to-read nutrition labeling for nearly all foods. The purpose of the new label isto reduce confusion and help consumers choose more healthful diets. <br>The United States Department of Agriculture (USDA) and the Department of Health and Human Service (HHS) have teamed up to produce the Food Guide Pyramid, which recommends eating a variety of foods, an appropriate number of calories, and a modest amount of fat-specifically, 30% or fewer of your total number of calories per day should be calories from fat, and only a third of those should be calories from saturated fat. For adults consuming 2000 calories per day, which works out to no more than 65 grams of fat, no more than 20 grams of which are saturated fat. <br>We want to know how many candy bars can fit into this daily diet. We found nutritional facts about every candy bar we could find. We also included some non-bar candies like M&Ms, Reese’s Pieces, Skittles, and S","75 rows, 17 columns.","SAS Institute Inc.","Descriptive Statistics, Graphic Analysis, Confidence Intervals","5 KB");
dataSetsNEW[10]=new Array("Statistics, General","sas7bdat","Cars","cars.sas7bdat","The data set contains information on cars such as weight, gas tank size, turning radius, horsepower and engine displacement for 116 cars from different countries.","116 rows, 8 columns.","SAS Institute Inc.","Descriptive Statistics, ANOVA, Graphic Analysis","61 KB");
dataSetsNEW[11]=new Array("Statistics, General","sas7bdat","Cars_1993","cars_1993.sas7bdat","A random sample of 92 1993 model cars is contained in this data set. The information for each car includes: manufacturer, model, type (sporty, van, small, midsize, large, or compact), price (in thousands of dollars), city mpg, highway mpg, engine size, horsepower, fuel tank size, weight, and origin (US or non-US). The data is excellent for doing descriptive statistics by groups or an ANOVA or regression with price as the response variable. Note that violations of the assumptions are probably present and transformation of the response variable is most likely necessary.","92 rows, 12 columns.","SAS Institute Inc.","Correlation, Regression, T-tests, Descriptive Statistics, Data Transformation, ANOVA, ANCOVA","13 KB");
dataSetsNEW[12]=new Array("Statistics, Data Management","sas7bdat","College","college.sas7bdat","The data is a collection of information on colleges and universities collected in the early 1990’s. The primary interest is in predicting graduation rates, the percent of students who graduate from the institution in four years. Potential predictor variables are tuition, type of college (public or private), and region of the country.","200 rows, 6 columns.","SAS Institute Inc.","Regression, ANOVA, ANCOVA, Graphic Analysis","17 KB");
dataSetsNEW[13]=new Array("Life Science, Biotechnology","sas7bdat","Colonoscopy","colonoscopy.sas7bdat","The data are from a prospective study of the findings of a colonoscopy screening study on individuals considered to be at high risk of colon cancer. The purpose of the study was to determine the role of past history in predicting the findings of a current colonoscopy. The cases considered here correspond to 406 individuals who had adenoma findings in previous colon examinations and who are therefore considered to be at high risk of a subsequent significant finding. The two variables in the data set are Finding (coded 0 for negative examination, 1 for small adenoma, and 2 for large adenoma) and Age. All ages have been rounded, ages 30-39 years coded as 35, ages 40-49 years coded as 45, etc.","406 rows, 2 columns.","SAS Institute Inc.","Regression, Graphic Analysis, Contingency Table","9 KB");
dataSetsNEW[14]=new Array("Statistics, General","sas7bdat","Corn","corn.sas7bdat","The data was collected to examine the effect of weather related phenomena on corn yield. The data set includes information on the total precipitation (in inches) for the year prior to the start of the growing season, the average daily temperature (in degrees Fahrenheit) for each of the months of May through August, the total rain (in inches) during each of the months June through August, and the corn yield (in bushels per acre). This information was collected for each of the years 1930 through 1962. The year is also included in the data set. You are interested in determining the relationship between the corn yield and the other variables.","33 rows, 10 columns.","SAS Institute Inc.","Regression, Correlation, Graphic Analysis","9 KB");
dataSetsNEW[15]=new Array("Statistics, General","sas7bdat","Cotton1","cotton1.sas7bdat","The total weight of a mature cotton boll can be divided into three parts: the weight of the seeds, the weight of the lint, and the weight of the bract. Lint and seed constitute the economic yield of cotton. In this data, the differences in thre three compontnts of the cotton bolls due to two varieties (VARIETY) and two plant spacings (SPACING) are studied. Five plants are chosen at random from each of the four treatment combinations. Two bolls are picked from each plant, and the weights of the seeds, linc, and bract are recorded.","40 rows, 6 columns.","SAS Institute Inc.","ANOVA","5 KB");
dataSetsNEW[16]=new Array("General","sas7bdat","Counts","counts.sas7bdat","This data is from an insect control experiment. The treatment design consisted of an untreated control group (TRT=0) and a 3x3 factorial for a total of 10 treatments. The experiment was conducted as a randomized complete block design with four blocks (BLOCK). The response variable was the insect count (COUNT). The variable CTL_TRT is coded 0 for control and 1 otherwise. The two treatment factors, A and B, have 3 levels each (1, 2, and 3) and both are coded 0 for the control.","40 rows, 6 columns.","SAS Institute Inc.","Regression","5 KB");
dataSetsNEW[17]=new Array("General","sas7bdat","Cultivar Inoculation","cult_inoc.sas7bdat","This data was collected to analyze the effect of three bacterial inoculation treatments (INOCULATION) applied to two cultivars of grasses (CULTIVAR) on dry weight yields (DRYWT). The experiment is a split-plot design with CULTIVAR (levels a and b) as the main plot factor and INOCULATION as the subplot factor. INOCULATION has the values control, live and dead.","24 rows, 4 columns.","SAS Institute Inc.","Graphic Analysis","5 KB");
dataSetsNEW[18]=new Array("General","sas7bdat","Defect Types","defecttypes.sas7bdat","You are in charge of the quality control effort at a bicycle manufacturer that specializes in limited production frames. The most popular model your company produces is a day touring model called the <em>Arribe!</em>, which is a racing-style frame for weekend warriors. <br>The seat tube has been a source of quality problems in the manufacturing plant in the past. This data set has information on reasons for rejection of the seat tubes during weeks 7 and 8 of a recent manufacturing cycle. You will use this data to determine if the pattern of defects is the same for both weeks.","1000 rows, 2 columns.","SAS Institute Inc.","Graphic Analysis, Quality Control","37 KB");
dataSetsNEW[19]=new Array("Statistics, General","sas7bdat","Drug","drug.sas7bdat","This is data from an experiment to evaluate the effect of four different drugs on blood pressure for individuals with one of three possible diseases. Each individual is administered one of the four drugs over a period of time and the increase in systolic blood pressure is recorded. You want to compare the average increase in blood pressure for the different drugs and diseases.","72 rows, 3 columns.","SAS Institute Inc.","General ANOVA","5 KB");
dataSetsNEW[20]=new Array("Statistics, General","sas7bdat","Drugs","drugs.sas7bdat","A pharmaceutical company compared effects of two drugs, A and B, on a clinical measurement called FLUSH. The studey untilized patients in 10 clinics in order to obtain respresentation from diverse patient populations. The variables in the data set are STUDY (which is the clinic identifier), TREATMENT, PATIENT, FLUSH0, FLUSH. The values of FLUSH0 were obtained prior to administration of the drugs. <br>If you assume the clinics are ranodmly selected from a population of clinics, then clinics becomes a random effect and the model is a mixed model. <br>","135 rows, 5 columns.","SAS Institute Inc.","Unbalanced ANOVA","13 KB");
dataSetsNEW[21]=new Array("Statistics, General","sas7bdat","Drugs1","drugs1.sas7bdat","A pharmaceutical company compared effects of two drugs, A and B, on a clinical measurement called FLUSH. The studey untilized patients in 10 clinics in order to obtain respresentation from diverse patient populations. The variables in the data set are STUDY (which is the clinic identifier), TREATMENT, PATIENT, FLUSH0, FLUSH. The values of FLUSH0 were obtained prior to administration of the drugs. (Note: this is the same data as the DRUGS data set with the addition of STUDY 41 which only had observations for drug B. Therefore, there is an empty cell associated with the STUDY 41, DRUG A combination.) <br>If you assume that the clinics were randomly selected from a larger population of clinics, then CLINIC is a random effect and the model becomes a mixed model. <br>","151 rows, 5 columns.","SAS Institute Inc.","Unbalanced ANOVA","9 KB");
dataSetsNEW[22]=new Array("Statistics, General","sas7bdat","Exercise","exercise.sas7bdat","You are an exercise physiologist who wants to determine whether stretching and wearing ankle weights has any effect on the value of treadmill exercise. You could test this hypothesis by measuring calories burned, average speed in meters per minute, and oxygen consumed in liters for a number of subjects who you have previously determined have roughly the same level of physical fitness, divided randomly into four groups: with or without ankle weights, and with or without a period of stretching before the exercise.","20 rows, 5 columns.","SAS Institute Inc.","General ANOVA","5 KB");
dataSetsNEW[23]=new Array("General","sas7bdat","File Marks","filemarks.sas7bdat","You are in charge of the quality control effort at a bicycle manufacturer that specializes in limited production frames. The most popular model your company produces is a day touring model called the <em>Arribe!</em>, which is a racing-style frame for weekend warriors. <br>The seat tubes of the bicycle frames are inspected. One of the most common problems with the tubes is stray file marks. Although this does not affect the functionality of the seat tube, it does affect the looks. The file marks data set contains 10 weeks of inspection data and has the total number of files marks for all bicycle tubes inspected during each of the ten weeks.","10 rows,   3 columns.","SAS Institute Inc.","Graphic Analysis, Quality Control","5 KB");
//dataSetsNEW[24]=new Array("Statistics, General","sas7bdat","Flaxoil","flaxoil.sas7bdat","The Flax Oil data set includes percentage measurements of oil content in flaxseed grown in each of four different locations for six different treatments. At each location one plant was inoculated with bacteria as a seedling, one plant in early bloom, one in full bloom, one at a lower dose in full bloom, and one when the plant was ripening. A sixth plant in each location was a control case, not inoculated at all. There was no replication of treatment by location combinations. The purpose of the experiment was to determine whether the treatments had any effect on the oil content of the flaxseed. The four locations represent the blocks in this experiment. One could consider that the blocking factor should be treated as a random effect, which would result in a mixed model.","24 rows, 3 columns.","R.G.D. Steel, McGraw-Hill","Mixed Model ANOVA, Randomized Complete Block ANOVA","5 KB");
dataSetsNEW[24]=new Array("Statistics, General","sas7bdat","fr_t7_3","fr_t7_3.sas7bdat","This data set has data from a bioassay involving two drugs, standard (STD) and treated (TRT) injected in varying dosages to 20 mice per treatment-dose combination. The response variable of interest is the number of mice (out of the 20) that are ALIVE versus the number DEAD. An alternative analysis approach is to use the base 2 log of dosage rather than the actual dosages. This is included as the variable X.","9 rows, 6 columns.","SAS Institute Inc.","Logistic ANCOVA","5 KB");
dataSetsNEW[25]=new Array("General","sas7bdat","Garments","garments.sas7bdat","Four materials (Material) used in permanent press garments are subjected to a test for weight loss (WTLOSS) and shrinkage (SHRINK). The materials are placed in a heart chamber that has four control settings or positions (POSITION). The test is conducted in four runs (RUN), with each material assigned to each of the four positions in one run of the experiment. The weight loss and shrinkage are measured on each sample after each test.","16 rows, 5 columns.","SAS Institute Inc.","Graphic Analysis","9 KB");
dataSetsNEW[26]=new Array("Statistics, General","sas7bdat","Grasses","grasses.sas7bdat","Three methods of promoting seed growth (METHOD) are applied to seed from each of five varieties (VARIETY). Six plots are planted with seed from each METHODxVARIETY combination. The resulting 90 pots were randomly placed in a growth chamber and the dry matter yields were measured after clipping at the end of four weeks. <br>The data are recorded in the data set with each of the six replicate measurements on the same row in the data set. Therefore, this data will have to be reorganized in order to analyze it as a two-way ANOVA. This can be done using the stack columns function in Enterprise Guide or with a data step program. (Note: the data set grasses1 contains the same data reorganized for analysis.) <br>In the case where you are interested in a whole population of varieties and these five are a random sample from that population, VARIETY would be treated as a random effect, resulting in a mixed model.<br>","15 rows, 9 columns.","SAS Institute Inc.","Two-way ANOVA","9 KB");
dataSetsNEW[27]=new Array("Statistics, General","sas7bdat","Grasses 1","grasses1.sas7bdat","Three methods of promoting seed growth (METHOD) are applied to seed from each of five varieties (VARIETY). Six plots are planted with seed from each METHODxVARIETY combination. The resulting 90 pots were randomly placed in a growth chamber and the dry matter yields were measured after clipping at the end of four weeks (YIELD). <br>Note: this data set contains the same data as the data set grasses except the data has been reorganized for analysis. <br>In the case where you are interested in a whole population of varieties and these five are a random sample from that population, VARIETY would be treated as a random effect, resulting in a mixed model. <br>","90 rows, 4 columns.","SAS Institute Inc.","Two-way ANOVA","5 KB");
dataSetsNEW[28]=new Array("Statistics, General","sas7bdat","Hospice","hospice.sas7bdat","Consider a study done to determine whether there was a change in the number of referrals received from physicians after a visit by a hospice marketing nurse. A portionof Ms. Skarzynski’s data about these hospice marketing visits includes physician ID, type of visit, type of practice, date, and change in referrals after one month (change1) and after three months (change3).","54 rows, 6 columns.","SAS Institute Inc.","ANOVA, Graphic Analysis","9 KB");
dataSetsNEW[29]=new Array("General","sas7bdat","Leppik","leppik.sas7bdat","This data is from a study evaluating a new treatment for epilepsy. The variable ID identifies each patient in the study. The treatments are TRT=0, a placebo, and TRT=1, an anti-epileptic drug. The response variable is the number of seizures over a two-week interval. For the eight weeks prior to placing the participants on treatment, the number of seizures was counted for each patient in order to form a baseline measurement (BASE). The patients' ages (AGE) in years are also included in the data set. The number of seizures was recorded for each of four two-week time intervals after being placed on the treatment and appears in the data set as Y1 through Y4. Two additional variables appear in the data set that might be used during the analysis. One is the log of age (LOG_AGE) and the other is the log of (BASE/4). This data set will need to be reorganized for analysis so that one post treatment observation appears on each row of the data set. This can be done with Enterprise Guide using the stack function, or with a data set. Also, the appropriately organized data is included in the data set SEIZURE.","59 rows, 10 columns.","SAS Institute Inc.","Regression, Graphic Analysis","9 KB");
dataSetsNEW[30]=new Array("Biotechnology","sas7bdat","Lipid Data","lipid.sas7bdat","Data has been collected from blood lipid screenings as well as patient history. Information such as gender, age, weight, total cholesterol level, blood pressure, coffee consumption, and history of heart disease was collected. The blood lipid screenings were conducted three months after the initial screenings. This data is rich for various analyses.","95 rows, 25 columns.","SAS Institute Inc.","Regression, Correlation, T-tests, Descriptive Statistics, ANOVA, Graphic Analysis","33 KB");
dataSetsNEW[31]=new Array("General","sas7bdat","Market","market.sas7bdat","This is data from 19 livestock auction markets, including the numbers of head of cattle sold (in thousands) (CATTLE), the cost of operations of the auction market (in thousands of dollars) (COST), and the market identifier (MARKETID). The object is to use simple linear regression to describes the relationship between the cost of operations to the number of cattle sold. COST will be the dependent variable and CATTLE the independent variable.","19 rows, 3 columns.","SAS Institute Inc.","Regression, Graphic Analysis","5 KB");
dataSetsNEW[32]=new Array("Statistics, General","sas7bdat","Methods","methods.sas7bdat","Five methods of providing irrigation (IRRIG) are used on an orange grove. At harvest, the fruit is weighed to determine if the method or irrigation affects fruit weight (FRUITWT). In this case, the grove was divided into eight blocks (BLOCK) to account for local variation in the grove. The assignment of the irrigation method to the trees within the block was done randomly and each of the irrigation methods appears in every block. Therefore, this is a randomized complete block design. The blocking factor can also be considered a random effect in which case the analysis would be done with a mixed model.","40 rows, 3 columns.","SAS Institute Inc.","ANOVA, Mixed Models","5 KB");
dataSetsNEW[33]=new Array("General","sas7bdat","Microbial Counts","microbgs.sas7bdat","Microbial counts are made on samples of ground beef in a study to assess sources of variation in numbers of microbes. Twenty packages of ground beef (PACKAGE) are purchased. Three samples are drawn from each package and two replicate counts are made on each sample. In the data set CT11 refers to the first sample, first replicate count for the package; CT12 refers to the first sample, second replicate count; CT21 refers to the second sample, first replicate count; and so on. Again this data set will have to be reorganized before analysis. (Note: the data set microbgs1 contains the reorganized data). Also, because of the skewed nature of the data, it is common to take the logarithm of the counts for analysis purposes. In this case, the sample is nested within the package and package is a random effect.","20 rows, 7 columns.","SAS Institute Inc.","Graphic Analysis, Mixed Models","9 KB");
dataSetsNEW[34]=new Array("General","sas7bdat","O Ring","o_ring.sas7bdat","Data documenting the presence or absence of primary O-ring thermal distress in the 23 shuttle launches preceding the Challenger mission were collected. The focus of this data is to determine if there is a relationship between the temperature at launch time and o-ring thermal distress. The variables in the data set are the flight number (FLT), the temperature at launch (TEMP), and an indicator variable for whether or not there was thermal distress during the launch (TD) (0=no distress, 1=distress). This data exists in an alternative form in the data set Challenger. In that case, the variables in the data set are temperature at launch (TEMP), the number of launches in which a thermal distress occurred for that temperature (TD), the total number of launches at that temperature (TOTAL), and the number of launches in which thermal distress did not occur at that temperature (NO_TD).","23 rows, 3 columns.","SAS Institute Inc.","Graphic Analysis","5 KB");
dataSetsNEW[35]=new Array("Business","sas7bdat","Oranges","oranges.sas7bdat","The data are from a study of the relationship between the price of oranges and sales per customer. The hypothesis is that sales vary as a function of price differences for different stores (STORE) and days of the week (DAY). The price is varied daily for two varieties of oranges. The variables P1 and P2 denote the prices for the two varieties, respectively. The variables Q1 and Q2 are the sales per customer of the corresponding varieties. Q1 and Q2 are used as the dependent variables, with STORE, DAY, P1, and P2 as the independent variables.","36 rows, 3 columns.","SAS Institute Inc.","ANCOVA, Graphic analysis","5 KB");
dataSetsNEW[36]=new Array("General","sas7bdat","Oysters","oysters.sas7bdat","Four bags with 10 oysters in each bag are randomly placed at each of five stations in the cooling water canal of a power-generating plant. Each location, or station, is considered a treatment and is represented by the varialbe TRT in the data set. Each bag is considered to be one experimental unit. Two stations are located in the intake canal, and two stations are located in the discharge canal, one at the top and the other at the bottom of each location. A single mid-depth station is located in a shallow portion of the bay near the power plant. The treatments are coded 1 through 5 in the data set as follows: (1) intake-bottom, (2) intake-surface, (3) discharge-bottom, (4) discharge-surface, and (5) bay. <br>The purpose of the experiment is to determine if exposure to water heated artificially affects growth and if the position in the water column (surface or bottom) affects growth. Stations in the intake canal act as controls for those in the discharge canal, which has a higher temperature. The station in th","20 rows, 4 columns.","SAS Institute Inc.","ANCOVA, Graphic analysis","5 KB");
//dataSetsNEW[38]=new Array("Statistics, Business<br>Data Management","htm","Aerosol Particle Size","pmc62.htm","This case study illustrates the use of Box-Jenkins modeling with aerosol particle size data. These data were collected from an aerosol mini-spray dryer device. The purpose of this device is to convert a slurry stream into deposited particles in a drying chamber. The device injects the slurry at high speed. The slurry is pulverized as it enters the drying chamber when it comes into contact with a hot gas stream at low humidity. The liquid contained in the pulverized slurry particles is vaporized, then transferred to the hot gas stream leaving behind dried small-sized particles. The response variable is particle size, which is collected equidistant in time. There are a variety of associated variables that may affect the injection process itself and hence the size and quality of the deposited particles. For this case study, we restrict our analysis to the response variable. The data set consists of particle sizes collected over time. The basic distributional properties of this process are","559 rows, 1 columns.","Antuan Negiz, The National Institute of Standards and technology","Correlation","0 KB");
dataSetsNEW[37]=new Array("Statistics, General","sas7bdat","Rats","rats.sas7bdat","Weight gains in rats given a special diet were measured at one (GAIN1), two (GAIN2), three (GAIN3), and four (GAIN4) weeks after beginning the administration of the diet. The question of interest is whether the rats’ weight gains stayed constant over the course of the experiment. In other words, were the average weight gains the same at each of the four weeks? An intercept only MANOVA model can be used to answer this question, or the data can be stacked and an ANOVA used.","10 rows, 4 columns.","SAS Institute Inc.","ANOVA, MANOVA","5 KB");
dataSetsNEW[38]=new Array("Statistics, General","sas7bdat","Teachers","teachers.sas7bdat","Student exam scores are collected, where each student is taught by one of three teachers. The purpose of the analysis is to compare the average scores for each of the three teachers. The teachers can be compared using either the score on the first exam (SCORE1) or the score on the second exam (SCORE2). <br>A multivariate ANOVA (MANOVA) can be used to determine if there is a difference between teachers when considering both SCORE1 and SCORE2 simultaneously. <br>","30 rows, 3 columns.","SAS Institute Inc.","ANOVA, MANOVA","5 KB");
dataSetsNEW[39]=new Array("Statistics, General","sas7bdat","Teaching","teaching.sas7bdat","A study was conducted in an industrial setting to test the effectiveness of several techniques for teaching the use of a respirator mask. Subjects were divided randomly into three groups: a control group that received no training in the use of the mask, a group that received a detailed instruction sheet, and a third group that attended a thirty minute class. The effectiveness of the mask was measured for each of the subjects before training and also one and two weeks after training. The purpose of the study is to determine whether, on average, there is any difference in effectiveness among the three teaching techniques.","28 rows, 4 columns.","SAS Institute Inc.","ANOVA, Graphic Analysis","5 KB");
dataSetsNEW[40]=new Array("Statistics, General","sas7bdat","Total Arrests","totarrests.sas7bdat","The data set is a record of the total number of arrests in the United States from 1970 through 1999. The variables in the data set are: year (YEAR), total number of arrests (TOTALARRESTS), total number of arrests by age group (AGE1 through AGE5), arrests per 100 thousand in population, total (ARRESTRATE) and by age group (AGE1RATE through AGE5RATE), total population of the U.S. on July 1 of the given year (POPULATION), and total population for each age group (AGE1POP through AGE5pop). <br>The data set could be used to generate descriptive statistics for the total population and by age group, or to do a time series analysis and predict total number of arrests for the population as a whole or by age group. These predictions might be used in assessing the need for judicial system infrastructure changes. Finally, the data could be used to compare age groups with an ANOVA, but the data would have to be reorganized to conduct such an analysis using the stack function in Enterprise Guide or a data step. <br>The data","30 rows, 19 columns.","SAS Institute Inc.","T-tests, Descriptive Statistics, ANOVA, Time Series","13 KB");
dataSetsNEW[41]=new Array("General","sas7bdat","Trees","tree.sas7bdat","In the 1930’s, the weights and trunk girths were measured for eight specimens from each of thirteen rootstocks, for a total of 104 tree specimens. The purpose is to determine if the girth and/or rootstock of the trees are useful in predicting the weight of trees. This would make it possible to get accurate estimates of weight without having to cut trees down and weigh them, a destructive and difficult process.","104 rows, 3 columns.","SAS Institute Inc.","Regression, ANOVA, ANCOVA, Graphic analysis","5 KB");
dataSetsNEW[42]=new Array("General","sas7bdat","Tube Angle","tubeangle.sas7bdat","You are in charge of the quality control effort at a bicycle manufacturer that specializes in limited production frames. The most popular model your company produces is a day touring model called the <em>Arribe!</em>, which is a racing-style frame for weekend warriors. The seat tube angle of a bicycle frame can dramatically affect the finished bicycle's handling characteristics. This is the angle formed by the intersection of the tube that holds the seat post with the top horizontal frame tube. A small seat tube angle endows the frame with forgiving handling characteristics. Weekend warriors want frames that are responsive and quick; they prefer frames with steep seat tube angles. The <em>Arribe!</em> is manufactured with these specifications in mind. The purpose of this analysis is to determine if the manufacturing process is in control. The target angle is 74 degrees, with specification limits of 73.7 and 74.3 degrees.","100 rows, 2 columns.","SAS Institute Inc.","Quality Control","5 KB");
dataSetsNEW[43]=new Array("General","sas7bdat","Tube Defects","tubedefects.sas7bdat","Often it is more cost-effective to simply evaluate whether an item is defective or not. This data is recorded from frame tubes prior to assembly. Frame tubes need to be meticulously filed, mitered and sanded before they are joined into a complete frame. The tube ends are then inspected to assure that they fit together properly. Rather than base your analyses on each of the measures that affect whether tubes fit together, you will analyze a single characteristic, specifically whether each individual tube is defective or not.","960 rows, 2 columns","SAS Institute Inc.","Graphic Analysis, Quality Control","21 KB");
dataSetsNEW[44]=new Array("Statistics, General","sas7bdat","Turnips","turnips.sas7bdat","To determine whether the moisture content of turnip green leaves is affected by time in storage, researchers classified the leaves of five turnip plants into five size groups, subjected these leaves to one of five lengths of storage time according to a specific pattern, and finally measured the moisture content of each leaf. Plant and leaf size are the blocking factors for this experiment.","25 rows, 4 columns.","R.G.D. Steel, McGraw-Hill","ANOVA with blocks","5 KB");
dataSetsNEW[45]=new Array("Statistics, General","sas7bdat","Veneer","veneer.sas7bdat","Consider an experiment to investigate the durability of three brands of synthetic wood veneer. This type of veneer is often used in office furniture and on kitchen countertops. To determine durability, samples of each of the three brands were subjected to a friction test. The amount of veneer material that is worn away due to friction is measured. The resulting wear measurement is recorded for each sample. Brands that have small measurements are desireable.","30 rows, 2 columns.","SAS Institute Inc.","ANOVA, Graphic Analysis","5 KB");
dataSetsNEW[46]=new Array("General","sas7bdat","WCGS (Western Collaborative Group Study)","wcgs.sas7bdat","The data are from a prospective study of the occurrence of coronary events-usually heart attacks. Covariates that may influence the risk of a coronary event include smoking, blood pressure history, and cholesterol level. These data are from a group of 3,154 male employees from ten California companies during 1960-1961. The original purpose of the study was to investigate the effects of behavior type and smoking habits on heart disease. After the recruitment, the study followed participants for nine years, although a few were lost to follow-up before the end of the study. The time variable of interest was the interval from entry into the study until the appearance, as determined by a medical expert, of coronary heart disease. The dataset contains event time and censor variables for 614 participants, as well as measurements of two covariates of interest: smoking behavior at study entry and behavior type. Individuals were classified into behavior types on the basis of an interview; in general terms, Type A behavior is characterized by aggressiveness and competitiveness, whereas Type B behavior is considered more relaxed and noncompetitive. In this subsample, events were observed in 60 individuals.","614 rows, 4 columns.","SAS Institute Inc.","Graphic Analysis, Survival","25 KB");
dataSetsNEW[47]=new Array("Statistics, General","sas7bdat","Westernrates","westernrates.sas7bdat","Different western cities are rated by nine criteria. For all but two of the variables, the higher the score, the better. For Housing and Crime, the lower the score, the better. You want to determine whether there is a linear correlation between any two of the criteria.","52 rows, 11 columns.","SAS Institute Inc.","Correlation, Graphic Analysis","13 KB");
dataSetsNEW[48]=new Array("Statistics, General","sas7bdat","Wine Tasting","wine.sas7bdat","In this experiment fifteen people rated six red wines. Each wine was rated using criteria commonly used to judge wine quality. The totals for each judge and wine were calculated. You will determine whether there is a difference in the quality of the wines as determined by the judges. <br>This data could also be used to rank the wines and then determine if there is agreement among the judges in terms of the ranks of the wines. <br>Some data manipulation will be necessary to conduct either of these analyses. <br>","15 rows, 7 columns.","SAS Institute Inc.","ANOVA, Measures of Agreement","90 KB");
dataSetsNEW[49]=new Array("General","sas7bdat","Writing","writing.sas7bdat","A university English department wants to know whether its first- year composition course is as effective for history and math majors as it is for English majors. We could do a simple analysis of variance with final class scores as the dependent variable and major as the factor. However, students could have differing verbal abilities, and we must control for that by including their Verbal SAT scores as a covariate. <br>The main question is whether the course is equally effective for students of different majors. Secondly, we want to estimate the average class score for students in each major. Finally, we want to know whether SAT scores are effective for controlling for variability among individual students. <br>","19 rows, 3 columns.","SAS Institute Inc.","ANOVA, ANCOVA, Graphic analysis","5 KB");



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terms_edu[15]="CONFIDENCEINTERV";
terms_edu[16]="CONFIDLIMITVAR";
terms_edu[17]="CONTINGENCYTABLE";
terms_edu[18]="CORRELATION/NP";
terms_edu[19]="CORRELATION/P";
terms_edu[20]="COVARIANCE";
terms_edu[21]="CRAMERSSTATISTIC";
terms_edu[22]="DEGREESOFFREEDOM";
terms_edu[23]="DEPENDENT";
terms_edu[24]="DESCRSTAT/NP";
terms_edu[25]="DESCRSTAT/P";
terms_edu[26]="DESIGN";
terms_edu[27]="DISCRETERANVAR";
terms_edu[28]="ESTIMATION";
terms_edu[29]="ESTIMATION/OTHER";
terms_edu[30]="EVENTS";
terms_edu[31]="EXPECTATION";
terms_edu[32]="EXPERDESIGN/TERM";
terms_edu[33]="FDISTRIBUTION";
terms_edu[34]="FREQDIAGRAM";
terms_edu[35]="FREQTABLE";
terms_edu[36]="FRIEDMANTEST";
terms_edu[37]="FTEST";
terms_edu[38]="GOODNESSFITTEST";
terms_edu[39]="GRADINGCURVE";
terms_edu[40]="GRAPH/PICTOGRAPH";
terms_edu[41]="HISTOGRAM";
terms_edu[42]="HYPERGEOMETRIC";
terms_edu[43]="I650/TEMPORARY";
terms_edu[44]="I650A";
terms_edu[45]="I650C";
terms_edu[46]="I650G";
terms_edu[47]="I650I";
terms_edu[48]="INDEPENDENT";
terms_edu[49]="INDEPENDSAMPLES";
terms_edu[50]="ITEMANALYSIS";
terms_edu[51]="KENDALLW";
terms_edu[52]="LSD";
terms_edu[53]="MANNWHITNEYTEST";
terms_edu[54]="MCNEMARTEST";
terms_edu[55]="MEAN";
terms_edu[56]="MEDIAN";
terms_edu[57]="MEDIANTEST";
terms_edu[58]="MISCELLANEOUS";
terms_edu[59]="MODE";
terms_edu[60]="MODEL";
terms_edu[61]="MULTIPLECOMPARIS";
terms_edu[62]="NONPARAMETRIC";
terms_edu[63]="NONRESPONSE";
terms_edu[64]="NONSAMPLINGERROR";
terms_edu[65]="NORMAL";
terms_edu[66]="ONETAIL/T";
terms_edu[67]="ONETAIL/Z";
terms_edu[68]="ONEWAY/CR";
terms_edu[69]="OTHER/AN";
terms_edu[70]="OTHER/CI";
terms_edu[71]="OTHER/CORREL/NP";
terms_edu[72]="OTHER/EVENTS";
terms_edu[73]="OTHER/N";
terms_edu[74]="OTHER/RV";
terms_edu[75]="OTHER/ST";
terms_edu[76]="OTHER/T";
terms_edu[77]="OTHER/Z";
terms_edu[78]="PARAMETRIC";
terms_edu[79]="PERCENTILE";
terms_edu[80]="PRECISION";
terms_edu[81]="PROBABILITY";
terms_edu[82]="PROBABILITYSAMPL";
terms_edu[83]="PROBDISTRIBUTION";
terms_edu[84]="PROBMODELS";
terms_edu[85]="PROPORTION";
terms_edu[86]="RANDOMVARIABLES";
terms_edu[87]="RANGE";
terms_edu[88]="REGRESSION";
terms_edu[89]="RELATEDSAMPLES";
terms_edu[90]="RELIABILITY";
terms_edu[91]="RHO";
terms_edu[92]="SAMPLE";
terms_edu[93]="SAMPLESIZE";
terms_edu[94]="SAMPLING";
terms_edu[95]="SAMPLINGDISTRIB";
terms_edu[96]="SAMPLINGERROR";
terms_edu[97]="SCATDIAGRAM/P";
terms_edu[98]="SCOPEOFINFERENCE";
terms_edu[99]="SIGNIFICANCE";
terms_edu[100]="SIGNIFICANCE/NP";
terms_edu[101]="SIGNTEST";
terms_edu[102]="SIMPLE/CI";
terms_edu[103]="SIMPLE/COR";
terms_edu[104]="SIMPLE/REG";
terms_edu[105]="SIMPLEDATASET";
terms_edu[106]="SIMPLEPROBABILIT";
terms_edu[107]="SIMPLERANDOM";
terms_edu[108]="SKEWNESS/P";
terms_edu[109]="STANDARDDEVIATIO";
terms_edu[110]="STANDARDERROR";
terms_edu[111]="STANDERROR/OTHER";
terms_edu[112]="STANDERROROFMEAN";
terms_edu[113]="STANDUNITS/NORMA";
terms_edu[114]="STATISTICS";
terms_edu[115]="STEMLEAFPLOT";
terms_edu[116]="SUMSOFSQUARES";
terms_edu[117]="TCHEBYSHEFFSTHM";
terms_edu[118]="TDISTRIBUTION";
terms_edu[119]="TESTCONSTRUCTION";
terms_edu[120]="TESTING";
terms_edu[121]="TESTOFHOMOGENEIT";
terms_edu[122]="TESTOFINDEPENDEN";
terms_edu[123]="TESTOFSIGNIFICAN";
terms_edu[124]="TESTTHEORY";
terms_edu[125]="TREATMENTASSIGN";
terms_edu[126]="TSCORE";
terms_edu[127]="TTEST";
terms_edu[128]="TWOTAIL/T";
terms_edu[129]="TWOTAIL/Z";
terms_edu[130]="TWOWAY/CR";
terms_edu[131]="TYPE2ERROR";
terms_edu[132]="UNBIASEDNESS";
terms_edu[133]="VALIDITY";
terms_edu[134]="VARIABILITY/NP";
terms_edu[135]="VARIABILITY/P";
terms_edu[136]="VARIANCE";
terms_edu[137]="VARIANCE/OTHER";
terms_edu[138]="WILCOXONSIGNRANK";
terms_edu[139]="ZSCORE";
terms_edu[140]="ZTEST";

var terms_nat=new Array();
terms_nat[0]="ANOVA";
terms_nat[1]="APOSTERIORI";
terms_nat[2]="APPLICATIONEX";
terms_nat[3]="BASICTERMS/REG";
terms_nat[4]="BASICTERMS/STATS";
terms_nat[5]="BAYESIAN";
terms_nat[6]="BINOMIAL";
terms_nat[7]="CENTRALLIMITTHM";
terms_nat[8]="CENTRALTENDENCY";
terms_nat[9]="CHISQUARE";
terms_nat[10]="COMBINATIONS";
terms_nat[11]="COMMONPITFALLS";
terms_nat[12]="COMPLETELYRANDOM";
terms_nat[13]="CONCEPT";
terms_nat[14]="CONCEPT/OTHER";
terms_nat[15]="CONDITIONALPROBA";
terms_nat[16]="CONFIDENCEINTERV";
terms_nat[17]="CONTINGENCYTABLE";
terms_nat[18]="CORRELATION/NP";
terms_nat[19]="CORRELATION/P";
terms_nat[20]="CUMULATIVEFN";
terms_nat[21]="DEGREESOFFREEDOM";
terms_nat[22]="DEPENDENT";
terms_nat[23]="DESCRSTAT/NP";
terms_nat[24]="DESCRSTAT/P";
terms_nat[25]="DESIGN";
terms_nat[26]="DISCRETERANVAR";
terms_nat[27]="ESTIMATION";
terms_nat[28]="EVENTS";
terms_nat[29]="EXPECTATION";
terms_nat[30]="EXPERDESIGN/TERM";
terms_nat[31]="EXPONENTIAL";
terms_nat[32]="FREQDIAGRAM";
terms_nat[33]="FREQTABLE";
terms_nat[34]="FRIEDMANTEST";
terms_nat[35]="FTEST";
terms_nat[36]="GOODNESSFITTEST";
terms_nat[37]="HISTOGRAM";
terms_nat[38]="HYPERGEOMETRIC";
terms_nat[39]="I650/TEMPORARY";
terms_nat[40]="I650A";
terms_nat[41]="I650C";
terms_nat[42]="I650G";
terms_nat[43]="I650I";
terms_nat[44]="INDEPENDENT";
terms_nat[45]="INDEPENDSAMPLES";
terms_nat[46]="JOINTPROBABILITY";
terms_nat[47]="LATINSQUARE";
terms_nat[48]="LSD";
terms_nat[49]="MANNWHITNEYTEST";
terms_nat[50]="MEAN";
terms_nat[51]="MEDIAN";
terms_nat[52]="MEDIANTEST";
terms_nat[53]="MISCELLANEOUS";
terms_nat[54]="MODE";
terms_nat[55]="MODEL";
terms_nat[56]="MULTIPLE/REG";
terms_nat[57]="MULTIPLECOMPARIS";
terms_nat[58]="NONBAYESIAN";
terms_nat[59]="NONPARAMETRIC";
terms_nat[60]="NORMAL";
terms_nat[61]="NORMALPAPER";
terms_nat[62]="ONETAIL/T";
terms_nat[63]="ONETAIL/Z";
terms_nat[64]="ONEWAY/CR";
terms_nat[65]="ONEWAY/RB";
terms_nat[66]="OTHER/CI";
terms_nat[67]="OTHER/N";
terms_nat[68]="OTHER/NP";
terms_nat[69]="OTHER/REG";
terms_nat[70]="OTHER/ST";
terms_nat[71]="OTHER/T";
terms_nat[72]="PARAMETRIC";
terms_nat[73]="PERCENTILE";
terms_nat[74]="POISSON";
terms_nat[75]="POPULATIONMODELS";
terms_nat[76]="PROBABILITY";
terms_nat[77]="PROBABILITYSAMPL";
terms_nat[78]="PROBDISTRIBUTION";
terms_nat[79]="PROBMODELS";
terms_nat[80]="PROPORTION";
terms_nat[81]="RANDOMIZEDBLOCK";
terms_nat[82]="RANDOMNUMBERS";
terms_nat[83]="RANDOMNUMBERS/S";
terms_nat[84]="RANDOMVARIABLES";
terms_nat[85]="REGRESSION";
terms_nat[86]="RELATEDSAMPLES";
terms_nat[87]="SAMPDIST/C";
terms_nat[88]="SAMPLE";
terms_nat[89]="SAMPLESIZE";
terms_nat[90]="SAMPLING";
terms_nat[91]="SAMPLINGDISTRIB";
terms_nat[92]="SCOPEOFINFERENCE";
terms_nat[93]="SIGNTEST";
terms_nat[94]="SIMPLE/CI";
terms_nat[95]="SIMPLE/COR";
terms_nat[96]="SIMPLE/REG";
terms_nat[97]="SIMPLEDATASET";
terms_nat[98]="SIMPLEPROBABILIT";
terms_nat[99]="SIMPLERANDOM";
terms_nat[100]="STANDARDDEVIATIO";
terms_nat[101]="STANDERROR/OTHER";
terms_nat[102]="STANDERROROFMEAN";
terms_nat[103]="STANDUNITS/NORMA";
terms_nat[104]="STATISTICS";
terms_nat[105]="TAU";
terms_nat[106]="TDISTRIBUTION";
terms_nat[107]="TESTING";
terms_nat[108]="TESTOFINDEPENDEN";
terms_nat[109]="TESTOFSIGNIFICAN";
terms_nat[110]="TREATMENTASSIGN";
terms_nat[111]="TTEST";
terms_nat[112]="TWOTAIL/T";
terms_nat[113]="TWOTAIL/Z";
terms_nat[114]="TWOWAY/CR";
terms_nat[115]="TYPE1ERROR";
terms_nat[116]="TYPE2ERROR";
terms_nat[117]="TYPICALSUMMARY";
terms_nat[118]="VARIABILITY/P";
terms_nat[119]="VARIANCE";
terms_nat[120]="VARIANCE/OTHER";
terms_nat[121]="WILCOXONSIGNRANK";
terms_nat[122]="ZSCORE";
terms_nat[123]="ZTEST";

var terms_psy=new Array();
terms_psy[0]="ANCOVA";
terms_psy[1]="ANOVA";
terms_psy[2]="APPLICATIONEX";
terms_psy[3]="ASSUMPTCUSTOMARY";
terms_psy[4]="BASICTERMS/REG";
terms_psy[5]="BASICTERMS/STATS";
terms_psy[6]="BINOMIAL";
terms_psy[7]="CHISQUARE";
terms_psy[8]="COEFFDETERMINAT";
terms_psy[9]="COMMONPITFALLS";
terms_psy[10]="COMPLETELYRANDOM";
terms_psy[11]="CONCEPT";
terms_psy[12]="CONFIDENCEINTERV";
terms_psy[13]="CONFIDLIMITVAR";
terms_psy[14]="CONTINGENCYTABLE";
terms_psy[15]="CONTINUOUSRANVAR";
terms_psy[16]="CORRELATION/NP";
terms_psy[17]="CORRELATION/P";
terms_psy[18]="COUNTING";
terms_psy[19]="CUMULATIVEFN";
terms_psy[20]="DESCRSTAT/NP";
terms_psy[21]="DESCRSTAT/P";
terms_psy[22]="DESIGN";
terms_psy[23]="DISCRETERANVAR";
terms_psy[24]="ESTIMATION";
terms_psy[25]="EXPERDESIGN/TERM";
terms_psy[26]="FREQTABLE";
terms_psy[27]="FRIEDMANTEST";
terms_psy[28]="FTEST";
terms_psy[29]="GRAPH/PICTOGRAPH";
terms_psy[30]="HISTOGRAM";
terms_psy[31]="ITEMANALYSIS";
terms_psy[32]="KOLMOGSMIRNOV";
terms_psy[33]="LATINSQUARE";
terms_psy[34]="MEAN";
terms_psy[35]="MEDIAN";
terms_psy[36]="MISCELLANEOUS";
terms_psy[37]="MULTIPLE/REG";
terms_psy[38]="NONPARAMETRIC";
terms_psy[39]="NORMAL";
terms_psy[40]="ONETAIL/T";
terms_psy[41]="ONEWAY/CR";
terms_psy[42]="ONEWAY/RB";
terms_psy[43]="OTHER/AN";
terms_psy[44]="OTHER/CI";
terms_psy[45]="OTHER/N";
terms_psy[46]="OTHER/NP";
terms_psy[47]="OTHER/T";
terms_psy[48]="PARAMETRIC";
terms_psy[49]="PERCENTILE";
terms_psy[50]="POLYNOMIAL/REG";
terms_psy[51]="PROBABILITY";
terms_psy[52]="PROBDISTRIBUTION";
terms_psy[53]="PROPORTION";
terms_psy[54]="RANDOMIZEDBLOCK";
terms_psy[55]="RANDOMVARIABLES";
terms_psy[56]="REGRESSION";
terms_psy[57]="RELIABILITY";
terms_psy[58]="RESIDUALS/AN";
terms_psy[59]="RHO";
terms_psy[60]="SAMPDIST/C";
terms_psy[61]="SAMPLE";
terms_psy[62]="SAMPLESIZE";
terms_psy[63]="SAMPLING";
terms_psy[64]="SCATDIAGRAM/NP";
terms_psy[65]="SCATDIAGRAM/P";
terms_psy[66]="SCOPEOFINFERENCE";
terms_psy[67]="SIGNIFICANCE";
terms_psy[68]="SIGNIFICANCE/NP";
terms_psy[69]="SIMPLE/CI";
terms_psy[70]="SIMPLE/COR";
terms_psy[71]="SIMPLE/REG";
terms_psy[72]="SIMPLEDATASET";
terms_psy[73]="SIMPLEPROBABILIT";
terms_psy[74]="SKEWNESS/NP";
terms_psy[75]="SKEWNESS/P";
terms_psy[76]="STANDERROR/OTHER";
terms_psy[77]="STANDERROROFMEAN";
terms_psy[78]="STANDUNITS/NORMA";
terms_psy[79]="STATISTICS";
terms_psy[80]="TAU";
terms_psy[81]="TDISTRIBUTION";
terms_psy[82]="TESTCONSTRUCTION";
terms_psy[83]="TESTING";
terms_psy[84]="TESTOFHOMOGENEIT";
terms_psy[85]="TESTOFINDEPENDEN";
terms_psy[86]="TESTOFSIGNIFICAN";
terms_psy[87]="TESTTHEORY";
terms_psy[88]="TREATMENTASSIGN";
terms_psy[89]="TTEST";
terms_psy[90]="TWOTAIL/T";
terms_psy[91]="VALIDITY";
terms_psy[92]="VARIABILITY/P";
terms_psy[93]="VARIANCE";
terms_psy[94]="VARIANCE/OTHER";
terms_psy[95]="WILCOXONSIGNRANK";
terms_psy[96]="ZSCORE";

var terms_soc=new Array();
terms_soc[0]="ANOVA";
terms_soc[1]="APPLICATIONEX";
terms_soc[2]="BASICTERMS/STATS";
terms_soc[3]="BAYESIAN";
terms_soc[4]="BINOMIAL";
terms_soc[5]="CENSUS";
terms_soc[6]="CENTRALTENDENCY";
terms_soc[7]="CHISQUARE";
terms_soc[8]="CHISQUAREDISTRIB";
terms_soc[9]="CLUSTER";
terms_soc[10]="COEFFDETERMINAT";
terms_soc[11]="COMBINATIONS";
terms_soc[12]="COMMONPITFALLS";
terms_soc[13]="COMPLETELYRANDOM";
terms_soc[14]="CONCEPT";
terms_soc[15]="CONDITIONALPROBA";
terms_soc[16]="CONFIDENCEINTERV";
terms_soc[17]="CONFIDLIMITVAR";
terms_soc[18]="CONTINGENCYTABLE";
terms_soc[19]="CONVENIENCE/CHUN";
terms_soc[20]="CORRELATION/NP";
terms_soc[21]="CORRELATION/P";
terms_soc[22]="CRAMERSSTATISTIC";
terms_soc[23]="DESCRSTAT/NP";
terms_soc[24]="DESCRSTAT/P";
terms_soc[25]="DESIGN";
terms_soc[26]="ESTIMATION";
terms_soc[27]="ESTIMATION/OTHER";
terms_soc[28]="EVENTS";
terms_soc[29]="EXPECTATION";
terms_soc[30]="EXPERDESIGN/TERM";
terms_soc[31]="FRAME";
terms_soc[32]="FTEST";
terms_soc[33]="GOODNESSFITTEST";
terms_soc[34]="I650/TEMPORARY";
terms_soc[35]="I650A";
terms_soc[36]="I650G";
terms_soc[37]="I650I";
terms_soc[38]="INDEPENDENT";
terms_soc[39]="JOINTPROBABILITY";
terms_soc[40]="JUDGEMENTSAMPLIN";
terms_soc[41]="KENDALLW";
terms_soc[42]="MCNEMARTEST";
terms_soc[43]="MEAN";
terms_soc[44]="MEDIAN";
terms_soc[45]="MISCELLANEOUS";
terms_soc[46]="MODE";
terms_soc[47]="MODEL";
terms_soc[48]="MULTIPLE/REG";
terms_soc[49]="NONBAYESIAN";
terms_soc[50]="NONPARAMETRIC";
terms_soc[51]="NONRESPONSE";
terms_soc[52]="NONSAMPLINGERROR";
terms_soc[53]="NORMAL";
terms_soc[54]="ONETAIL/T";
terms_soc[55]="ONETAIL/Z";
terms_soc[56]="ONEWAY/CR";
terms_soc[57]="ONEWAY/RB";
terms_soc[58]="OPERATIONALFAULT";
terms_soc[59]="OTHER/CI";
terms_soc[60]="OTHER/N";
terms_soc[61]="OTHER/NP";
terms_soc[62]="OTHER/REG";
terms_soc[63]="OTHER/V";
terms_soc[64]="OTHER/Z";
terms_soc[65]="PARAMETRIC";
terms_soc[66]="PERMUTATIONS";
terms_soc[67]="POLYNOMIAL/REG";
terms_soc[68]="POPULATION";
terms_soc[69]="PROBABILITY";
terms_soc[70]="PROBABILITYSAMPL";
terms_soc[71]="PROBDISTRIBUTION";
terms_soc[72]="PROPORTION";
terms_soc[73]="RANDOMIZEDBLOCK";
terms_soc[74]="REGRESSION";
terms_soc[75]="RELATEDSAMPLES";
terms_soc[76]="RHO";
terms_soc[77]="SAMPLE";
terms_soc[78]="SAMPLESIZE";
terms_soc[79]="SAMPLING";
terms_soc[80]="SAMPLINGERROR";
terms_soc[81]="SCATDIAGRAM/P";
terms_soc[82]="SCOPEOFINFERENCE";
terms_soc[83]="SIGNIFICANCE";
terms_soc[84]="SIGNIFICANCE/NP";
terms_soc[85]="SIMPLE/CI";
terms_soc[86]="SIMPLE/COR";
terms_soc[87]="SIMPLE/REG";
terms_soc[88]="SIMPLEPROBABILIT";
terms_soc[89]="SIMPLERANDOM";
terms_soc[90]="STANDARDDEVIATIO";
terms_soc[91]="STANDERROR/OTHER";
terms_soc[92]="STANDERROROFMEAN";
terms_soc[93]="STANDUNITS/NORMA";
terms_soc[94]="STATISTICS";
terms_soc[95]="STEMLEAFPLOT";
terms_soc[96]="STRATIFIED";
terms_soc[97]="SUMSOFSQUARES";
terms_soc[98]="TAU";
terms_soc[99]="TESTCONSTRUCTION";
terms_soc[100]="TESTING";
terms_soc[101]="TESTOFHOMOGENEIT";
terms_soc[102]="TESTOFINDEPENDEN";
terms_soc[103]="TESTOFSIGNIFICAN";
terms_soc[104]="TESTTHEORY";
terms_soc[105]="TREATMENTASSIGN";
terms_soc[106]="TTEST";
terms_soc[107]="TWOTAIL/T";
terms_soc[108]="TWOTAIL/Z";
terms_soc[109]="TYPE1ERROR";
terms_soc[110]="TYPICALSUMMARY";
terms_soc[111]="VARIABILITY/NP";
terms_soc[112]="VARIANCE";
terms_soc[113]="VARIANCE/OTHER";
terms_soc[114]="WILCOXONSIGNRANK";
terms_soc[115]="ZSCORE";
terms_soc[116]="ZTEST";

var terms_gen=new Array();
terms_gen[0]="ACCURACY";
terms_gen[1]="ANCOVA";
terms_gen[2]="ANOVA";
terms_gen[3]="APOSTERIORI";
terms_gen[4]="APPLICATIONEX";
terms_gen[5]="APRIORI";
terms_gen[6]="ASSUMPTCUSTOMARY";
terms_gen[7]="BARCHART/P";
terms_gen[8]="BASICTERMS/PROB";
terms_gen[9]="BASICTERMS/REG";
terms_gen[10]="BASICTERMS/STATS";
terms_gen[11]="BAYESIAN";
terms_gen[12]="BINOMIAL";
terms_gen[13]="CENSUS";
terms_gen[14]="CENTRALLIMITTHM";
terms_gen[15]="CENTRALTENDENCY";
terms_gen[16]="CHISQUARE";
terms_gen[17]="CHISQUAREDISTRIB";
terms_gen[18]="CLASSINTERVAL";
terms_gen[19]="CLUSTER";
terms_gen[20]="COEFFDETERMINAT";
terms_gen[21]="COEFFVARIATION";
terms_gen[22]="COMBINATIONS";
terms_gen[23]="COMMONPITFALLS";
terms_gen[24]="COMPLETELYRANDOM";
terms_gen[25]="COMPUTERPROGRAMS";
terms_gen[26]="COMPUTFORMULA";
terms_gen[27]="CONCEPT";
terms_gen[28]="CONCEPT/OTHER";
terms_gen[29]="CONDITIONALPROBA";
terms_gen[30]="CONFIDENCEINTERV";
terms_gen[31]="CONFIDLIMITVAR";
terms_gen[32]="CONTINGENCYTABLE";
terms_gen[33]="CONTINUOUSRANVAR";
terms_gen[34]="CONVENIENCE/CHUN";
terms_gen[35]="CORRELATION/NP";
terms_gen[36]="CORRELATION/P";
terms_gen[37]="COUNTING";
terms_gen[38]="COVARIANCE";
terms_gen[39]="CRAMERSSTATISTIC";
terms_gen[40]="CUMULATIVEFN";
terms_gen[41]="DEGREESOFFREEDOM";
terms_gen[42]="DENSITYFN";
terms_gen[43]="DEPENDENT";
terms_gen[44]="DESCRSTAT/NP";
terms_gen[45]="DESCRSTAT/P";
terms_gen[46]="DESIGN";
terms_gen[47]="DISCRETERANVAR";
terms_gen[48]="DUNCANS";
terms_gen[49]="EFFICIENCY";
terms_gen[50]="ESTIMATION";
terms_gen[51]="ESTIMATION/OTHER";
terms_gen[52]="EVENTS";
terms_gen[53]="EXPECTATION";
terms_gen[54]="EXPERDESIGN/TERM";
terms_gen[55]="EXPONENTIAL";
terms_gen[56]="FDISTRIBUTION";
terms_gen[57]="FRAME";
terms_gen[58]="FRATIO";
terms_gen[59]="FREQDIAGRAM";
terms_gen[60]="FREQTABLE";
terms_gen[61]="FRIEDMANTEST";
terms_gen[62]="FTEST";
terms_gen[63]="GEOMETRIC";
terms_gen[64]="GOODNESSFITTEST";
terms_gen[65]="GRADINGCURVE";
terms_gen[66]="GRAPH/PICTOGRAPH";
terms_gen[67]="HISTOGRAM";
terms_gen[68]="HYPERGEOMETRIC";
terms_gen[69]="I650/TEMPORARY";
terms_gen[70]="I650A";
terms_gen[71]="I650C";
terms_gen[72]="I650E";
terms_gen[73]="I650G";
terms_gen[74]="I650I";
terms_gen[75]="INDEPENDENT";
terms_gen[76]="INDEPENDSAMPLES";
terms_gen[77]="INTERACTION";
terms_gen[78]="ITEMANALYSIS";
terms_gen[79]="JOINTDISTRIBUTIO";
terms_gen[80]="JOINTPROBABILITY";
terms_gen[81]="JUDGEMENTSAMPLIN";
terms_gen[82]="KENDALLW";
terms_gen[83]="KOLMOGSMIRNOV";
terms_gen[84]="KRUSKALWALLIS";
terms_gen[85]="LATINSQUARE";
terms_gen[86]="LSD";
terms_gen[87]="MANNWHITNEYTEST";
terms_gen[88]="MAXLIKELIHOOD";
terms_gen[89]="MCNEMARTEST";
terms_gen[90]="MEAN";
terms_gen[91]="MEANFREQDIAGRAM";
terms_gen[92]="MEDIAN";
terms_gen[93]="MEDIANTEST";
terms_gen[94]="MINVARIANCE";
terms_gen[95]="MISCELLANEOUS";
terms_gen[96]="MODE";
terms_gen[97]="MODEL";
terms_gen[98]="MOMENT";
terms_gen[99]="MOMENTGENFN";
terms_gen[100]="MULTIPLE/COR";
terms_gen[101]="MULTIPLE/REG";
terms_gen[102]="MULTIPLECOMPARIS";
terms_gen[103]="MULTIVARIATE/AN";
terms_gen[104]="MULTIVARIATE/P";
terms_gen[105]="Multiple";
terms_gen[106]="NEWMANKEULS";
terms_gen[107]="NONBAYESIAN";
terms_gen[108]="NONPARAMETRIC";
terms_gen[109]="NONRESPONSE";
terms_gen[110]="NONSAMPLINGERROR";
terms_gen[111]="NORMAL";
terms_gen[112]="NORMALPAPER";
terms_gen[113]="NWAY/LS";
terms_gen[114]="NWAY/RB";
terms_gen[115]="ONETAIL/T";
terms_gen[116]="ONETAIL/Z";
terms_gen[117]="ONEWAY/CR";
terms_gen[118]="ONEWAY/LS";
terms_gen[119]="ONEWAY/RB";
terms_gen[120]="OPERATIONALFAULT";
terms_gen[121]="ORDERSTATISTICS";
terms_gen[122]="OTHER/AN";
terms_gen[123]="OTHER/CI";
terms_gen[124]="OTHER/CORREL/NP";
terms_gen[125]="OTHER/EVENTS";
terms_gen[126]="OTHER/N";
terms_gen[127]="OTHER/NP";
terms_gen[128]="OTHER/REG";
terms_gen[129]="OTHER/RV";
terms_gen[130]="OTHER/S";
terms_gen[131]="OTHER/ST";
terms_gen[132]="OTHER/T";
terms_gen[133]="OTHER/V";
terms_gen[134]="OTHER/Z";
terms_gen[135]="OTHESTANDARDERRO";
terms_gen[136]="PARAMETRIC";
terms_gen[137]="PERCENTILE";
terms_gen[138]="PERMUTATIONS";
terms_gen[139]="POISSON";
terms_gen[140]="POLYNOMIAL/REG";
terms_gen[141]="POPULATION";
terms_gen[142]="POPULATIONMODELS";
terms_gen[143]="POWER";
terms_gen[144]="PRECISION";
terms_gen[145]="PREDICTION";
terms_gen[146]="PROBABILITY";
terms_gen[147]="PROBABILITYSAMPL";
terms_gen[148]="PROBDISTRIBUTION";
terms_gen[149]="PROBFUNCTION";
terms_gen[150]="PROBMODELS";
terms_gen[151]="PROBSAMPCONCEPT";
terms_gen[152]="PROPORTION";
terms_gen[153]="Q#";
terms_gen[154]="RANDOMIZEDBLOCK";
terms_gen[155]="RANDOMNUMBERS";
terms_gen[156]="RANDOMNUMBERS/S";
terms_gen[157]="RANDOMVARIABLES";
terms_gen[158]="RANDOMVARIATION";
terms_gen[159]="RANGE";
terms_gen[160]="REGRESSION";
terms_gen[161]="RELATEDSAMPLES";
terms_gen[162]="RELIABILITY";
terms_gen[163]="RESIDUALS/AN";
terms_gen[164]="RESIDUALS/REG";
terms_gen[165]="RHO";
terms_gen[166]="SAMPDIST/C";
terms_gen[167]="SAMPLE";
terms_gen[168]="SAMPLESIZE";
terms_gen[169]="SAMPLING";
terms_gen[170]="SAMPLINGDISTRIB";
terms_gen[171]="SAMPLINGERROR";
terms_gen[172]="SCATDIAGRAM/NP";
terms_gen[173]="SCATDIAGRAM/P";
terms_gen[174]="SCHEFFESSMETHOD";
terms_gen[175]="SCOPEOFINFERENCE";
terms_gen[176]="SEQUENTIAL";
terms_gen[177]="SIGNIFICANCE";
terms_gen[178]="SIGNIFICANCE/NP";
terms_gen[179]="SIGNTEST";
terms_gen[180]="SIMP";
terms_gen[181]="SIMPLE/CI";
terms_gen[182]="SIMPLE/COR";
terms_gen[183]="SIMPLE/REG";
terms_gen[184]="SIMPLEDATASET";
terms_gen[185]="SIMPLEPROBABILIT";
terms_gen[186]="SIMPLERANDOM";
terms_gen[187]="SKEWNESS/NP";
terms_gen[188]="SKEWNESS/P";
terms_gen[189]="SPECIALCASE/PROB";
terms_gen[190]="STANDARDDEVIATIO";
terms_gen[191]="STANDARDERROR";
terms_gen[192]="STANDERROR/OTHER";
terms_gen[193]="STANDERROROFMEAN";
terms_gen[194]="STANDUNITS/NORMA";
terms_gen[195]="STATISTICS";
terms_gen[196]="STEMLEAFPLOT";
terms_gen[197]="STRATIFIED";
terms_gen[198]="STRUCTURALLIMIT";
terms_gen[199]="SUFFICIENCY";
terms_gen[200]="SUMSOFSQUARES";
terms_gen[201]="TAU";
terms_gen[202]="TCHEBYSHEFFSTHM";
terms_gen[203]="TDISTRIBUTION";
terms_gen[204]="TESTCONSTRUCTION";
terms_gen[205]="TESTING";
terms_gen[206]="TESTOFHOMOGENEIT";
terms_gen[207]="TESTOFINDEPENDEN";
terms_gen[208]="TESTOFSIGNIFICAN";
terms_gen[209]="TESTTHEORY";
terms_gen[210]="TRATIO";
terms_gen[211]="TREATMENTASSIGN";
terms_gen[212]="TSCORE";
terms_gen[213]="TTEST";
terms_gen[214]="TUKEYSHSD";
terms_gen[215]="TWOTAIL/T";
terms_gen[216]="TWOTAIL/Z";
terms_gen[217]="TWOWAY/CR";
terms_gen[218]="TWOWAY/LS";
terms_gen[219]="TWOWAY/RB";
terms_gen[220]="TYPE1ERROR";
terms_gen[221]="TYPE2ERROR";
terms_gen[222]="TYPICALPIC/GRAPH";
terms_gen[223]="TYPICALSUMMARY";
terms_gen[224]="UNBIASEDNESS";
terms_gen[225]="UNH/ONLY";
terms_gen[226]="UNIFORM";
terms_gen[227]="VALIDITY";
terms_gen[228]="VARI";
terms_gen[229]="VARIABILITY/NP";
terms_gen[230]="VARIABILITY/P";
terms_gen[231]="VARIANCE";
terms_gen[232]="VARIANCE/OTHER";
terms_gen[233]="WILCOXONSIGNRANK";
terms_gen[234]="ZSCORE";
terms_gen[235]="ZTEST";

var terms_all=new Array();
terms_all[0]="PROBABILITY";
terms_all[1]="BASICTERMS/PROB";
terms_all[2]="PROBMODELS";
terms_all[3]="PROBDISTRIBUTION";
terms_all[4]="MULTIVARIATE/P";
terms_all[5]="UNIFORM";
terms_all[6]="JOINTDISTRIBUTIO";
terms_all[7]="TDISTRIBUTION";
terms_all[8]="FDISTRIBUTION";
terms_all[9]="CHISQUAREDISTRIB";
terms_all[10]="STANDUNITS/NORMA";
terms_all[11]="TSCORE";
terms_all[12]="ZSCORE";
terms_all[13]="OTHER/ST";
terms_all[14]="POISSON";
terms_all[15]="BINOMIAL";
terms_all[16]="NORMAL";
terms_all[17]="NORMALPAPER";
terms_all[18]="GRADINGCURVE";
terms_all[19]="OTHER/N";
terms_all[20]="MOMENTGENFN";
terms_all[21]="DENSITYFN";
terms_all[22]="CUMULATIVEFN";
terms_all[23]="CONCEPT/OTHER";
terms_all[24]="PROBFUNCTION";
terms_all[25]="GEOMETRIC";
terms_all[26]="HYPERGEOMETRIC";
terms_all[27]="EXPONENTIAL";
terms_all[28]="EXPECTATION";
terms_all[29]="RANDOMVARIABLES";
terms_all[30]="RANDOMNUMBERS";
terms_all[31]="OTHER/RV";
terms_all[32]="DISCRETERANVAR";
terms_all[33]="CONTINUOUSRANVAR";
terms_all[34]="CONDITIONALPROBA";
terms_all[35]="NONBAYESIAN";
terms_all[36]="BAYESIAN";
terms_all[37]="COMBINATIONS";
terms_all[38]="PERMUTATIONS";
terms_all[39]="COUNTING";
terms_all[40]="SIMPLEPROBABILIT";
terms_all[41]="EVENTS";
terms_all[42]="OTHER/EVENTS";
terms_all[43]="INDEPENDENT";
terms_all[44]="DEPENDENT";
terms_all[45]="JOINTPROBABILITY";
terms_all[46]="STATISTICS";
terms_all[47]="BASICTERMS/STATS";
terms_all[48]="NONPARAMETRIC";
terms_all[49]="CHISQUARE";
terms_all[50]="MCNEMARTEST";
terms_all[51]="GOODNESSFITTEST";
terms_all[52]="CONTINGENCYTABLE";
terms_all[53]="CONFIDLIMITVAR";
terms_all[54]="MEDIANTEST";
terms_all[55]="TESTOFINDEPENDEN";
terms_all[56]="TESTOFHOMOGENEIT";
terms_all[57]="CORRELATION/NP";
terms_all[58]="RHO";
terms_all[59]="TAU";
terms_all[60]="KENDALLW";
terms_all[61]="CRAMERSSTATISTIC";
terms_all[62]="OTHER/CORREL/NP";
terms_all[63]="SIGNIFICANCE/NP";
terms_all[64]="DESCRSTAT/NP";
terms_all[65]="MEDIAN";
terms_all[66]="MODE";
terms_all[67]="VARIABILITY/NP";
terms_all[68]="OTHER/V";
terms_all[69]="RANGE";
terms_all[70]="SCATDIAGRAM/NP";
terms_all[71]="BARCHART/NP";
terms_all[72]="SKEWNESS/NP";
terms_all[73]="POPULATIONMOD/NP";
terms_all[74]="OTHER/NP";
terms_all[75]="SIGNTEST";
terms_all[76]="WILCOXONSIGNRANK";
terms_all[77]="MANNWHITNEYTEST";
terms_all[78]="KOLMOGSMIRNOV";
terms_all[79]="KRUSKALWALLIS";
terms_all[80]="FRIEDMANTEST";
terms_all[81]="ORDERSTATISTICS";
terms_all[82]="CONCEPT";
terms_all[83]="DESIGN";
terms_all[84]="TESTING";
terms_all[85]="RELATEDSAMPLES";
terms_all[86]="INDEPENDSAMPLES";
terms_all[87]="ESTIMATION";
terms_all[88]="SAMPDIST/C";
terms_all[89]="CONSISTENCY";
terms_all[90]="SUFFICIENCY";
terms_all[91]="EFFICIENCY";
terms_all[92]="UNBiASEDNESS";
terms_all[93]="CONFIDENCEINTERV";
terms_all[94]="SIMPLE/CI";
terms_all[95]="OTHER/CI";
terms_all[96]="MAXLIKELIHOOD";
terms_all[97]="MINVARIANCE";
terms_all[98]="ESTIMATION/OTHER";
terms_all[99]="POPULATION";
terms_all[100]="CENTRALLIMITTHM";
terms_all[101]="POWER";
terms_all[102]="TESTOFSIGNIFICAN";
terms_all[103]="TYPE1ERROR";
terms_all[104]="TYPE2ERROR";
terms_all[105]="TCHEBYSHEFFSTHM";
terms_all[106]="PREDICTION";
terms_all[107]="SCOPEOFINFERENCE";
terms_all[108]="PARAMETRIC";
terms_all[109]="DESCRSTAT/P";
terms_all[110]="CENTRALTENDENCY";
terms_all[111]="SCATDIAGRAM/P";
terms_all[112]="PROPORTION";
terms_all[113]="BARCHART/P";
terms_all[114]="MOMENT";
terms_all[115]="MEAN";
terms_all[116]="VARIABILITY/P";
terms_all[117]="STANDARDDEVIATIO";
terms_all[118]="VARIANCE";
terms_all[119]="COVARIANCE";
terms_all[120]="STANDERROROFMEAN";
terms_all[121]="POPULATIONMODELS";
terms_all[122]="HISTOGRAM";
terms_all[123]="FREQDIAGRAM";
terms_all[124]="PERCENTILE";
terms_all[125]="FREQTABLE";
terms_all[126]="CLASSINTERVAL";
terms_all[127]="SKEWNESS/P";
terms_all[128]="STANDERROR/OTHER";
terms_all[129]="STEMLEAFPLOT";
terms_all[130]="VARIANCE/OTHER";
terms_all[131]="GRAPH/PICTOGRAPH";
terms_all[132]="COEFFVARIATION";
terms_all[133]="TTEST";
terms_all[134]="ONETAIL/T";
terms_all[135]="TWOTAIL/T";
terms_all[136]="OTHER/T";
terms_all[137]="REGRESSION";
terms_all[138]="MULTIPLE/REG";
terms_all[139]="SIMPLE/REG";
terms_all[140]="RESIDUALS/REG";
terms_all[141]="STANDARDERROR";
terms_all[142]="MULTIVARIATE/REG";
terms_all[143]="OTHER/REG";
terms_all[144]="BASICTERMS/REG";
terms_all[145]="POLYNOMIAL/REG";
terms_all[146]="COEFFDETERMINAT";
terms_all[147]="ANCOVA";
terms_all[148]="CORRELATION/P";
terms_all[149]="SIGNIFICANCE";
terms_all[150]="PARTIAL";
terms_all[151]="MULTIPLE/COR";
terms_all[152]="SIMPLE/COR";
terms_all[153]="BISERIAL";
terms_all[154]="ANOVA";
terms_all[155]="OTHER/AN";
terms_all[156]="RESIDUALS/AN";
terms_all[157]="DEGREESOFFREEDOM";
terms_all[158]="COMPUTFORMULA";
terms_all[159]="FTEST";
terms_all[160]="TREATMENTASSIGN";
terms_all[161]="LATINSQUARE";
terms_all[162]="TWOWAY/LS";
terms_all[163]="ONEWAY/LS";
terms_all[164]="NWAY/LS";
terms_all[165]="RANDOMIZEDBLOCK";
terms_all[166]="TWOWAY/RB";
terms_all[167]="ONEWAY/RB";
terms_all[168]="NWAY/RB";
terms_all[169]="COMPLETELYRANDOM";
terms_all[170]="TWOWAY/CR";
terms_all[171]="ONEWAY/CR";
terms_all[172]="NWAY/CR";
terms_all[173]="MULTIVARIATE/AN";
terms_all[174]="SUMSOFSQUARES";
terms_all[175]="EXPERDESIGN/TERM";
terms_all[176]="INTERACTION";
terms_all[177]="MULTIPLECOMPARIS";
terms_all[178]="APRIORI";
terms_all[179]="TRATIO";
terms_all[180]="FRATIO";
terms_all[181]="DUNNS";
terms_all[182]="APOSTERIORI";
terms_all[183]="LSD";
terms_all[184]="TUKEYSHSD";
terms_all[185]="SCHEFFESSMETHOD";
terms_all[186]="NEWMANKEULS";
terms_all[187]="DUNCANS";
terms_all[188]="DUNNETTS";
terms_all[189]="ITEMANALYSIS";
terms_all[190]="ZTEST";
terms_all[191]="ONETAIL/Z";
terms_all[192]="TWOTAIL/Z";
terms_all[193]="OTHER/Z";
terms_all[194]="SAMPLING";
terms_all[195]="PROBABILITYSAMPL";
terms_all[196]="PROBSAMPCONCEPT";
terms_all[197]="SIMPLERANDOM";
terms_all[198]="STRATIFIED";
terms_all[199]="CLUSTER";
terms_all[200]="SEQUENTIAL";
terms_all[201]="SAMPLINGDISTRIB";
terms_all[202]="SAMPLESIZE";
terms_all[203]="SAMPLE";
terms_all[204]="CENSUS";
terms_all[205]="FRAME";
terms_all[206]="SAMPLINGERROR";
terms_all[207]="PRECISION";
terms_all[208]="UNCORRELATED";
terms_all[209]="RANDOMVARIATION";
terms_all[210]="RANDOMNUMBERS/S";
terms_all[211]="CONVENIENCE/CHUN";
terms_all[212]="JUDGEMENTSAMPLIN";
terms_all[213]="NONSAMPLINGERROR";
terms_all[214]="ACCURACY";
terms_all[215]="OTHER/S";
terms_all[216]="NONRESPONSE";
terms_all[217]="STRUCTURALLIMIT";
terms_all[218]="OPERATIONALFAULT";
terms_all[219]="TESTTHEORY";
terms_all[220]="RELIABILITY";
terms_all[221]="VALIDITY";
terms_all[222]="TESTCONSTRUCTION";
terms_all[223]="MISCELLANEOUS";
terms_all[224]="MODEL";
terms_all[225]="ASSUMPTCUSTOMARY";
terms_all[226]="APPLICATIONEX";
terms_all[227]="TYPICALPIC/GRAPH";
terms_all[228]="SIMPLEDATASET";
terms_all[229]="TYPICALSUMMARY";
terms_all[230]="COMMONPITFALLS";
terms_all[231]="COMPUTERPROGRAMS";

function subsetTree(aname) {
	var total=0;
	var nottotal=0;
	var notin="";
//aname="bio";
   myarray = eval("terms_" + aname); 
   mynum = myarray.length; // alert(mynum);
   // run through the check boxes 
   var docCheck = document.body.getElementsByTagName("input");
   for (n=0; n<=docCheck.length-1; n++) { 
      if (docCheck[n].type=="checkbox") {
	  flag=0;
      // run through the array 
         for (var i=0; i<mynum; i++) {
            myvalue = myarray[i]; 
            if (myvalue == docCheck[n].value) flag=1;
         }
         if(flag == 1) { 
		    docCheck[n].parentNode.style.display="block"; 
			total++; 
		 }
	     else {
		     notin+=docCheck[n].value + "<br>"; 
		     docCheck[n].parentNode.style.display="none"; 
			 nottotal++;
	     }
	  }
   }
 //  newWindow = window.open('','NotIn','top=0,left=0,width=550,height=750,resizable=1,scrollbars=yes');
 //  newWindow.document.write(notin); 
 //  newWindow.document.close(); 

  // alert(notin);
 //  alert("in="+total);
 //  alert("out="+nottotal);
}

function showPopupQuestions() {
alert('showPopupQuestions');
   var docDiv = document.body.getElementsByTagName("div"); 
   for (n=0; n<=docDiv.length-1; n++) { 
      if(docDiv[n].className == "statquestions") docDiv[n].style.display="block";
   }
      var docPre = document.body.getElementsByTagName("pre"); 
      for (n=0; n<=docPre.length-1; n++) { 
         docPre[n].style.display="block";
      }
}