Chapter Review Quiz SAS


Combining Data Sets

Select the best answer for each question. When you are finished, click Submit Quiz.

  1. Which of the following statements is true about merging SAS data sets by using the DATA step?

     a.   Merging combines observations from two or more data sets into a single observation in new data set.
     b.   SAS can merge data sets based on the position of observations in the original data set or by the values of one or more common variables.
     c.   Match-merging is merging by values of one or more common variables.
     d.   To match-merge data sets, all input data sets must be sorted or indexed on the BY variable(s).
     e.   all of the above

  2. Which of the following programs concatenates the data sets sales and products, in that order?

     a.   
    date newsales;
   set products sales;
run;
     b.   
    date newsales;
   set sales products;
run;
     c.   
    date newsales;
   set sales;
   set products;
run;

  3. If you run this DATA step, what observations does the data set bonuses contain? 

    date bonuses;
   merge managers staff;
   by EmpID;
run;
     a.   all of the observations from managers, and only those observations from staff with matching values for EmpID
     b.   all of the observations from staff, and only those observations from managers with matching values for EmpID
     c.   all observations from staff and all observations from managers, whether or not they have matching values
     d.   only those observations from staff and manager with matching values for EmpID

  4. If you concatenate the data sets below in the order shown, what is the value of Sale in observaton 2 of the new data set?

    reps
    ID
    Name
    1
    Nay Rong
    2
    Kelly Windsor
    3
    Julio Meraz
    4
    Richard Krabill
    		close
    ID
    Sale
    1
    $28,000
    2
    $30,000
    2
    $40,000
    3
    $15,000
    3
    $20,000
    3
    $25,000
    4
    $35,000
     a.   missing
     b.   $30,000
     c.   $40,000
     d.   You cannot concatenate these data sets.

  5. What happens if you submit the following program to merge donors1 and donors2, shown below? 

    data merged; 
   merge donors1 donors2;
   by ID;
run;
    donors1
    ID
    Type
    Units
    2304
    		 O
    16
    1129
    		 A
    48
    1129
    		 A
    50
    1129
    		 A
    57
    2486
    B
    63
    		donors2
    ID
    Code
    Units
    6488
    		 65
    27
    1129
    		 63
    32
    5438
    		 62
    39
    2304
    		 61
    45
    1387
    		 64
    67

     a.   The merged data set contains some missing values because not all observations have matching observations in the other data set.
     b.   The merged data set contains eight observations.
     c.   The DATA step produces errors.

  6. Suppose you want to concatenate these data sets. Which DATA step creates an output data set that combines the values of Color and Hue in the single variable Color?

    widget1
    Tag
    Color
    Model
    77904
    		 blue
    AB42
    56012
    		 red
    BA25
    35499
    		 orange
    FC36
    		widget2
    Tag
    Hue
    Model
    89325
    		 red
    SP17
    65888
    		 yellow
    BA12
    00167
    		 green
    PG20

     a.   
    data widgets_all;
   set widget1(rename=(Color=Hue))
       widget2;
run;
     b.   
    data widgets_all;
   set widget1
       widget2(rename=(Hue=Color));
run;
     c.   
    data widgets_all;
   set widget1
       widget2(Hue=color);
run;

  7. What is the syntax error in this DATA step? 

    data returns_qtr1;
   set returns_jan(rename=(ID=CustID)
                  (Return=Item)) 
       returns_feb(rename=(Dt=Date))
       returns_mar;
run;
     a.   You cannot specify more than two data sets in the SET statement.
     b.   There are too many sets of parentheses in the RENAME= option.
     c.   You cannot specify multiple variables in the RENAME= option.
     d.   The BY statement is missing.

  8. In the second iteration of this DATA step, after the data has been merged, what are the values of C and A? 

    data client_amount;
   merge clients(in=C) 
         amounts(in=A);
   by Name;
run;
    clients
    Name
    EmpID
    Ankerton
    11123
    Davis
    22293
    Masters
    33351
    Wolmer
    44483
    		amounts
    Name
    Date
    Amt
    Ankerton
    08OCT96
    92
    Ankerton
    15OCT96
    43
    Davis
    04OCT96
    16
    Masters
    .
    27
    Thomas
    21OCT96
    15

     a.   C=1, A=0
     b.   C=0, A=1
     c.   C=1, A=1
     d.   missing
     e.   unknown

  9. If you run this DATA step, what observations does the data set bonuses contain? 

    data bonuses;
   merge managers (in=M)
         staff (in=S);
   by EmpID;
   if M=0 and S=1;
run;
     a.   only the observations from staff that have no match in managers
     b.   only the observations from managers that have no match in staff
     c.   all observations from both managers and staff, whether or not they match
     d.   no observations

  10. What is the relationship of the data set first to the data set second when merged by the variable ID?

    first
    Name
    ID
    Age
    Togar
    121150
    39
    Kylie
    121152
    34
    Birin
    121153
    32
    Gloria
    121154
    12
    James
    121155
    36
    Gene
    121156
    28
    Tom
    121157
    27
    		second
    ID
    Date
    121150
    02/15/05
    121152
    05/22/07
    121153
    03/04/06
    121154
    11/22/05
    121155
    07/08/06
    121156
    12/15/06
    121157
    04/30/07

     a.   one-to-one
     b.   one-to-many
     c.   many-to-one
     d.   many-to-many
     e.   non-matching


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