• Contents
  • About
  • What’s New in the Base SAS 9.4 Statistical Procedures
    • Overview
    • FREQ Procedure Enhancements
    • UNIVARIATE Procedure Enhancements
  • 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
        • Common Risk Difference
        • 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 Basic Summary Plots
      • 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


ProductRelease
Base SAS9.4_M4
Type
Usage and Reference
Copyright Date
November 2016
Last Updated
22Nov2016