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| The UNIVARIATE Procedure |
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- Overview: UNIVARIATE Procedure
- Getting Started: UNIVARIATE Procedure
- Syntax: UNIVARIATE Procedure
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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
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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
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