List of Outputs

Chapter 1: The CORR Procedure

Output 1.1.1: Simple Statistics

Output 1.1.2: Pearson Correlation Coefficients

Output 1.1.3: Spearman Correlation Coefficients

Output 1.1.4: Kendalls Tau-b Correlation Coefficients

Output 1.1.5: Hoeffdings Dependence Coefficients

Output 1.1.6: Symmetric Scatter Plot Matrix (Experimental)

Output 1.2.1: Simple Statistics

Output 1.2.2: Sum-of-squares and Crossproducts

Output 1.2.3: Variances and Covariances

Output 1.2.4: Pearson Correlation Coefficients

Output 1.2.5: Rectangular Matrix Plot (Experimental)

Output 1.3.1: Sample Correlations

Output 1.3.2: Correlation Statistics Using Fishers z Transformation

Output 1.3.3: One-sided Correlation Analysis Using Fishers z Transformation

Output 1.4.1: Fishers Test for H : =

Output 1.4.2: Fishers Correlation Statistics

Output 1.4.3: Test of Equality of Observed Correlations

Output 1.4.4: Combined Correlation Estimate

Output 1.5.1: Simple Statistics

Output 1.5.2: Pearson Correlation Coefficients

Output 1.7.3: Scatter Plot Matrix (Experimental)

Output 1.5.3: Cronbachs Coefficient Alpha

Output 1.5.4: Cronbachs Coefficient Alpha with Deleted Variables

Output 1.6.1: Pearson Correlation Coefficients

Output 1.6.2: OUTP= Data Set with Pearson Correlations

Output 1.7.1: Simple Statistics

Output 1.7.2: Pearson Correlation Coefficients

Output 1.7.4: Scatter Plot with Prediction Ellipses (Experimental)

Output 1.7.5: Scatter Plot with Prediction Ellipses (Experimental)

Output 1.7.6: Scatter Plot with Confidence Ellipses (Experimental)

Output 1.8.1: Descriptive Statistics

Output 1.8.2: Pearson Partial Correlation Coefficients

Output 1.8.3: Partial Residual Scatter Plot (Experimental)

Chapter 2: The FREQ Procedure

Output 2.1.1: Frequency Tables

Output 2.1.2: Crosstabulation Table

Output 2.1.3: OUT= Data Set

Output 2.2.1: One-Way Frequency Table with BY Groups

Output 2.3.1: Binomial Proportion for Eye Color

Output 2.3.2: Binomial Proportion for Hair Color

Output 2.4.1: Contingency Table

Output 2.4.2: Chi-Square Statistics

Output 2.4.3: Relative Risk

Output 2.5.1: Contingency Table

Output 2.5.2: Chi-Square Statistics

Output 2.5.3: Output Data Set

Output 2.6.1: Cochran-Mantel-Haenszel Statistics

Output 2.6.2: CMH OptionRelative Risks

Output 2.6.3: CMH OptionBreslow-Day Test

Output 2.7.1: Contingency Table

Output 2.7.2: Measures of Association

Output 2.7.3: Trend Test

Output 2.8.1: CMH StatisticsStratifying by Subject

Output 2.8.2: CMH StatisticsNo Stratification

Output 2.9.1: One-Way Frequency Tables

Output 2.9.2: Measures of Agreement

Output 2.9.3: Cochrans Q

Chapter 3: The UNIVARIATE Procedure

Output 3.1.1: Display Basic Measures and Quantiles

Output 3.2.1: Table of Modes Display

Output 3.2.2: Default Output (Without MODES Option)

Output 3.3.1: Blood Pressure Extreme Observations

Output 3.3.2: Blood Pressure Extreme Values

Output 3.4.1: Table of Frequencies

Output 3.5.1: Ozone Plots for BY Group Site = 102

Output 3.5.2: Ozone Plots for BY Group Site = 134

Output 3.5.3: Ozone Plots for BY Group Site = 137

Output 3.5.4: Ozone Side-by-Side Boxplot for All BY Group

Output 3.6.1: Table of Moments

Output 3.7.1: Listing of Output Data Set Means

Output 3.7.2: Listing of Output Data Set StrengthStats

Output 3.8.1: Listing of Output Data Set PctlStrength

Output 3.8.2: Listing of Output Data Set Pctls

Output 3.9.1: Default 95% Confidence Limits

Output 3.9.2: 90% Confidence Limits

Output 3.10.1: Normal-Based Quantile Confidence Limits

Output 3.10.2: Distribution-Free Quantile Confidence Limits

Output 3.11.1: Computation of Trimmed and Winsorized Means

Output 3.11.2: Computation of Robust Estimates of Scale

Output 3.12.1: Tests for Location with MU0=66 and LOCCOUNT

Output 3.13.1: Sign Test for ScoreChange

Output 3.14.1: Histogram for Plating Thickness

Output 3.15.1: Partial Listing of Data Set Channel

Output 3.15.2: Histogram for Length Ignoring Lot Source

Output 3.15.3: Comparison by Lot Source

Output 3.16.1: Two-Way Comparative Histogram

Output 3.17.1: Comparative Histograms

Output 3.18.1: Table of Bin Percentages Requested with MIDPERCENTS Option

Output 3.18.2: Histogram with ENDPOINTS= Option

Output 3.18.3: Histogram with MIDPOINTS= and RTINCLUDE Options

Output 3.18.4: The OUTHISTOGRAM= Data Set OutMdpts

Output 3.19.1: Summary of Fitted Normal Distribution

Output 3.19.2: Summary of Fitted Normal Distribution (cont.)

Output 3.19.3: Histogram Superimposed with Normal Curve

Output 3.20.1: Fitting Normal Curves to a Comparative Histogram

Output 3.21.1: Superimposing a Histogram with a Fitted Beta Curve

Output 3.21.2: Summary of Fitted Beta Distribution

Output 3.22.1: Superimposing a Histogram with Fitted Curves

Output 3.22.2: Summary of Fitted Lognormal Distribution

Output 3.22.3: Summary of Fitted Lognormal Distribution (cont.)

Output 3.22.4: Summary of Fitted Weibull Distribution

Output 3.22.5: Summary of Fitted Gamma Distribution

Output 3.23.1: Multiple Kernel Density Estimates

Output 3.24.1: Three-Parameter Lognormal Fit

Output 3.25.1: Preliminary Estimates of , ƒ , and

Output 3.25.2: Final Estimates of , ƒ , and

Output 3.25.3: The Data Set OutCalc

Output 3.25.4: Histogram with Annotated Folded Normal Curve

Output 3.26.1: Probability Plot Based on Lognormal Distribution with ƒ =0.7

Output 3.26.2: Probability Plot Based on Lognormal Distribution with ƒ =0.9

Output 3.26.3: Probability Plot Based on Lognormal Distribution with ƒ =1.1

Output 3.26.4: Probability Plot Based on Lognormal Distribution with Estimated ƒ

Output 3.27.1: Normal Probability Plot Created with Graphics Device

Output 3.27.2: Summary of Fitted Lognormal Distribution

Output 3.28.1: Normal Quantile-Quantile Plot for Distance

Output 3.29.1: Adding a Distribution Reference Line to a Q-Q Plot

Output 3.30.1: Normal Quantile-Quantile Plot of Nonnormal Data

Output 3.31.1: Lognormal Quantile-Quantile Plot ( ƒ =0.2)

Output 3.31.2: Lognormal Quantile-Quantile Plot ( ƒ =0.5)

Output 3.31.3: Lognormal Quantile-Quantile Plot ( ƒ =0.8)

Output 3.31.4: Lognormal Quantile-Quantile Plot ( ƒ =est, =est, =5)

Output 3.32.1: Lognormal Q-Q Plot Identifying Percentiles

Output 3.33.1: Two-Parameter Lognormal Q-Q Plot for Diameters

Output 3.34.1: Three-Parameter Weibull Q-Q Plot

Output 3.34.2: Two-Parameter Weibull Q-Q Plot for = 24