The UNIVARIATE Procedure
- Overview
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Getting Started
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Syntax
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DetailsMissing ValuesRoundingDescriptive StatisticsCalculating the ModeCalculating PercentilesTests for LocationConfidence Limits for Parameters of the Normal DistributionRobust EstimatorsCreating Line Printer PlotsCreating High-Resolution GraphicsUsing the CLASS Statement to Create Comparative PlotsPositioning InsetsFormulas for Fitted Continuous DistributionsGoodness-of-Fit TestsKernel Density EstimatesConstruction of Quantile-Quantile and Probability PlotsInterpretation of Quantile-Quantile and Probability PlotsDistributions for Probability and Q-Q PlotsEstimating Shape Parameters Using Q-Q PlotsEstimating Location and Scale Parameters Using Q-Q PlotsEstimating Percentiles Using Q-Q PlotsInput Data SetsOUT= Output Data Set in the OUTPUT StatementOUTHISTOGRAM= Output Data SetOUTKERNEL= Output Data SetOUTTABLE= Output Data SetTables for Summary StatisticsODS Table NamesODS Tables for Fitted DistributionsODS GraphicsComputational Resources
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ExamplesComputing Descriptive Statistics for Multiple VariablesCalculating ModesIdentifying Extreme Observations and Extreme ValuesCreating a Frequency TableCreating Plots for Line Printer OutputAnalyzing a Data Set With a FREQ VariableSaving Summary Statistics in an OUT= Output Data SetSaving Percentiles in an Output Data SetComputing Confidence Limits for the Mean, Standard Deviation, and VarianceComputing Confidence Limits for Quantiles and PercentilesComputing Robust EstimatesTesting for LocationPerforming a Sign Test Using Paired DataCreating a HistogramCreating a One-Way Comparative HistogramCreating a Two-Way Comparative HistogramAdding Insets with Descriptive StatisticsBinning a HistogramAdding a Normal Curve to a HistogramAdding Fitted Normal Curves to a Comparative HistogramFitting a Beta CurveFitting Lognormal, Weibull, and Gamma CurvesComputing Kernel Density EstimatesFitting a Three-Parameter Lognormal CurveAnnotating a Folded Normal CurveCreating Lognormal Probability PlotsCreating a Histogram to Display Lognormal FitCreating a Normal Quantile PlotAdding a Distribution Reference LineInterpreting a Normal Quantile PlotEstimating Three Parameters from Lognormal Quantile PlotsEstimating Percentiles from Lognormal Quantile PlotsEstimating Parameters from Lognormal Quantile PlotsComparing Weibull Quantile PlotsCreating a Cumulative Distribution PlotCreating a P-P Plot
- References
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 Plots for Line Printer Output
- 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