Contents
About
What’s New in the Base SAS 9.3 and 9.4 Statistical Procedures
Enhancements
CORR Procedure
FREQ Procedure
UNIVARIATE Procedure
What’s Changed
FREQ Procedure
References
The CORR Procedure
Overview: CORR Procedure
Getting Started: CORR Procedure
Syntax: CORR Procedure
PROC CORR Statement
BY Statement
FREQ Statement
ID Statement
PARTIAL Statement
VAR Statement
WEIGHT Statement
WITH Statement
Details: CORR Procedure
Pearson Product-Moment Correlation
Spearman Rank-Order Correlation
Kendall’s Tau-b Correlation Coefficient
Hoeffding Dependence Coefficient
Partial Correlation
Fisher’s z Transformation
Polychoric Correlation
Polyserial Correlation
Cronbach’s Coefficient Alpha
Confidence and Prediction Ellipses
Missing Values
In-Database Computation
Output Tables
Output Data Sets
ODS Table Names
ODS Graphics
Examples: CORR Procedure
Computing Four Measures of Association
Computing Correlations between Two Sets of Variables
Analysis Using Fisher’s z Transformation
Applications of Fisher’s z Transformation
Computing Polyserial Correlations
Computing Cronbach’s Coefficient Alpha
Saving Correlations in an Output Data Set
Creating Scatter Plots
Computing Partial Correlations
References
The FREQ Procedure
Overview: FREQ Procedure
Getting Started: FREQ Procedure
Frequency Tables and Statistics
Agreement Study
Syntax: FREQ Procedure
PROC FREQ Statement
BY Statement
EXACT Statement
OUTPUT Statement
TABLES Statement
TEST Statement
WEIGHT Statement
Details: FREQ Procedure
Inputting Frequency Counts
Grouping with Formats
Missing Values
In-Database Computation
Statistical Computations
Definitions and Notation
Chi-Square Tests and Statistics
Measures of Association
Binomial Proportion
Risks and Risk Differences
Odds Ratio and Relative Risks for 2 x 2 Tables
Cochran-Armitage Test for Trend
Jonckheere-Terpstra Test
Tests and Measures of Agreement
Cochran-Mantel-Haenszel Statistics
Gail-Simon Test for Qualitative Interactions
Exact Statistics
Computational Resources
Output Data Sets
Displayed Output
ODS Table Names
ODS Graphics
Examples: FREQ Procedure
Output Data Set of Frequencies
Frequency Dot Plots
Chi-Square Goodness-of-Fit Tests
Binomial Proportions
Analysis of a 2x2 Contingency Table
Output Data Set of Chi-Square Statistics
Cochran-Mantel-Haenszel Statistics
Cochran-Armitage Trend Test
Friedman’s Chi-Square Test
Cochran’s Q Test
References
The UNIVARIATE Procedure
Overview: UNIVARIATE Procedure
Getting Started: UNIVARIATE Procedure
Capabilities of PROC UNIVARIATE
Summarizing a Data Distribution
Exploring a Data Distribution
Modeling a Data Distribution
Syntax: UNIVARIATE Procedure
PROC UNIVARIATE Statement
BY Statement
CDFPLOT Statement
CLASS Statement
FREQ Statement
HISTOGRAM Statement
ID Statement
INSET Statement
OUTPUT Statement
PPPLOT Statement
PROBPLOT Statement
QQPLOT Statement
VAR Statement
WEIGHT Statement
Dictionary of Common Options
Details: UNIVARIATE Procedure
Missing Values
Rounding
Descriptive Statistics
Calculating the Mode
Calculating Percentiles
Tests for Location
Confidence Limits for Parameters of the Normal Distribution
Robust Estimators
Creating Line Printer Plots
Creating High-Resolution Graphics
Using the CLASS Statement to Create Comparative Plots
Positioning Insets
Formulas for Fitted Continuous Distributions
Goodness-of-Fit Tests
Kernel Density Estimates
Construction of Quantile-Quantile and Probability Plots
Interpretation of Quantile-Quantile and Probability Plots
Distributions for Probability and Q-Q Plots
Estimating Shape Parameters Using Q-Q Plots
Estimating Location and Scale Parameters Using Q-Q Plots
Estimating Percentiles Using Q-Q Plots
Input Data Sets
OUT= Output Data Set in the OUTPUT Statement
OUTHISTOGRAM= Output Data Set
OUTKERNEL= Output Data Set
OUTTABLE= Output Data Set
Tables for Summary Statistics
ODS Table Names
ODS Tables for Fitted Distributions
ODS Graphics
Computational Resources
Examples: UNIVARIATE Procedure
Computing Descriptive Statistics for Multiple Variables
Calculating Modes
Identifying Extreme Observations and Extreme Values
Creating a Frequency Table
Creating Plots for Line Printer Output
Analyzing a Data Set With a FREQ Variable
Saving Summary Statistics in an OUT= Output Data Set
Saving Percentiles in an Output Data Set
Computing Confidence Limits for the Mean, Standard Deviation, and Variance
Computing Confidence Limits for Quantiles and Percentiles
Computing Robust Estimates
Testing for Location
Performing a Sign Test Using Paired Data
Creating a Histogram
Creating a One-Way Comparative Histogram
Creating a Two-Way Comparative Histogram
Adding Insets with Descriptive Statistics
Binning a Histogram
Adding a Normal Curve to a Histogram
Adding Fitted Normal Curves to a Comparative Histogram
Fitting a Beta Curve
Fitting Lognormal, Weibull, and Gamma Curves
Computing Kernel Density Estimates
Fitting a Three-Parameter Lognormal Curve
Annotating a Folded Normal Curve
Creating Lognormal Probability Plots
Creating a Histogram to Display Lognormal Fit
Creating a Normal Quantile Plot
Adding a Distribution Reference Line
Interpreting a Normal Quantile Plot
Estimating Three Parameters from Lognormal Quantile Plots
Estimating Percentiles from Lognormal Quantile Plots
Estimating Parameters from Lognormal Quantile Plots
Comparing Weibull Quantile Plots
Creating a Cumulative Distribution Plot
Creating a P-P Plot
References
Product
Release
Base SAS
9.4
Type
Usage and Reference
Copyright Date
July 2013
Last Updated
08Jul2013