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The UNIVARIATE Procedure

Overview
Getting Started
Capabilities of PROC UNIVARIATE Summarizing a Data Distribution Exploring a Data Distribution Modeling a Data Distribution
Syntax
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
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
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

Examples: UNIVARIATE Procedure

Subsections:

4.1 Computing Descriptive Statistics for Multiple Variables
4.2 Calculating Modes
4.3 Identifying Extreme Observations and Extreme Values
4.4 Creating a Frequency Table
4.5 Creating Basic Summary Plots
4.6 Analyzing a Data Set With a FREQ Variable
4.7 Saving Summary Statistics in an OUT= Output Data Set
4.8 Saving Percentiles in an Output Data Set
4.9 Computing Confidence Limits for the Mean, Standard Deviation, and Variance
4.10 Computing Confidence Limits for Quantiles and Percentiles
4.11 Computing Robust Estimates
4.12 Testing for Location
4.13 Performing a Sign Test Using Paired Data
4.14 Creating a Histogram
4.15 Creating a One-Way Comparative Histogram
4.16 Creating a Two-Way Comparative Histogram
4.17 Adding Insets with Descriptive Statistics
4.18 Binning a Histogram
4.19 Adding a Normal Curve to a Histogram
4.20 Adding Fitted Normal Curves to a Comparative Histogram
4.21 Fitting a Beta Curve
4.22 Fitting Lognormal, Weibull, and Gamma Curves
4.23 Computing Kernel Density Estimates
4.24 Fitting a Three-Parameter Lognormal Curve
4.25 Annotating a Folded Normal Curve
4.26 Creating Lognormal Probability Plots
4.27 Creating a Histogram to Display Lognormal Fit
4.28 Creating a Normal Quantile Plot
4.29 Adding a Distribution Reference Line
4.30 Interpreting a Normal Quantile Plot
4.31 Estimating Three Parameters from Lognormal Quantile Plots
4.32 Estimating Percentiles from Lognormal Quantile Plots
4.33 Estimating Parameters from Lognormal Quantile Plots
4.34 Comparing Weibull Quantile Plots
4.35 Creating a Cumulative Distribution Plot
4.36 Creating a P-P Plot

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