LITMIR.BIZ

      List of Programs

       Chapter 1

       Program 1.1: Using PROC PRINT to List the Observations in a SAS Data Set

       Program 1.2: Using PROC CONTENTS to Display the Data Descriptor Portion of a SAS Data Set

       Program 1.3: Reading Data from a Text File That Uses Spaces as Delimiters

       Program 1.4: Using PROC PRINT to List the Observations in Data Set Sample2

       Program 1.5: Reading a CSV File

       Chapter 2

       Program 2.1: Generating Descriptive Statistics with PROC MEANS

       Program 2.2: Statistics Broken Down by a Classification Variable

       Program 2.3: Demonstrating the PRINTALLTYPES Option with PROC MEANS

       Program 2.4: Computing a 95% Confidence Interval

       Program 2.5: Producing Histograms and Probability Plots Using PROC UNIVARIATE

       Program 2.6: Using PROC SGPLOT to Produce a Histogram

       Program 2.7: Using SGPLOT to Produce a Horizontal Box Plot

       Program 2.8: Displaying Outliers in a Box Plot

       Program 2.9: Labeling Outliers on a Box Plot

       Program 2.10: Displaying Multiple Box Plots for Each Value of a Categorical Variable

       Chapter 3

       Program 3.1: Computing Frequencies and Percentages Using PROC FREQ

       Program 3.2: Demonstrating the NOCUM Tables Option

       Program 3.3: Demonstrating the Effect of the MISSING Option with PROC FREQ

       Program 3.4: Computing Frequencies on a Continuous Variable

       Program 3.5: Writing a Format for Gender, SBP, and DBP

       Program 3.6: Generating a Bar Chart Using PROC GCHART

       Program 3.7: Generating a Bar Chart Using PROC SGPLOT

       Program 3.8: Using ODS to Create PDF Output

       Program 3.9: Creating a Cross-Tabulation Table Using PROC FREQ

       Program 3.10: Changing the Order of Values in a PROC FREQ Table By Using Formats

       Chapter 4

       Program 4.1: Creating a Scatter Plot Using PROC GPLOT

       Program 4.2: Adding Gender Information to the Plot

       Program 4.3: Using PROC SGPLOT to Produce a Scatter Plot

       Program 4.4: Adding Gender to the Scatter Plot Using PROC SGPLOT

       Program 4.5: Demonstrating the PLOT Statement of PROC SGSCATTER

       Program 4.6: Demonstrating the COMPARE Statement of PROC SGSCATTER

       Program 4.7: Switching the x- and y-Axes and Adding a GROUP= Option

       Program 4.8: Producing a Scatter Plot Matrix

       Chapter 5

       Program 5.1: Conducting a One-Sample t-test Using PROC TTEST

       Program 5.2: Demonstrating ODS Graphics with PROC TTEST

       Program 5.3: Conducting a One-Sample t-test

       Program 5.4: Conducting a One-Sample Test with a Nonzero Null Hypothesis

       Program 5.5: Testing Whether a Variable is Normally Distributed

       Chapter 6

       Program 6.1: Conducting a Two-Sample t-test

       Program 6.2: Demonstrating ODS Graphics

       Program 6.3: Selecting Plots Using the PLOT Option for PROC TTEST

       Program 6.4: Conducting a Paired t-test

       Program 6.5: Using ODS Plots to Test t-Test Assumptions

       Chapter 7

       Program 7.1: Running a One-Way ANOVA

       Program 7.2: Requesting Multiple Comparison Tests

       Program 7.3: Using ODS Graphics to Produce a Diffogram1

       Program 7.4: Performing a Two-Way Factorial Design

       Program 7.5: Analyzing a Factorial Design with Significant Interactions

       Program 7.6: Analyzing a Randomized Block Design

       Chapter 8

       Program 8.1: Producing Correlations between Two Sets of Variables

       Program 8.2: Producing a Correlation Matrix

       Program 8.3: Creating HTML Output That Contains Data Tips

       Program 8.4: Generating Spearman Rank Correlations

       Program 8.5: Running a Simple Linear Regression Model

       Program 8.6: Displaying Influential Observations

       Program 8.7: Predicting Values Using the Regression Equation

       Program 8.8: Using PROC REG to Compute Predicted Values

       Program 8.9: Describing a More Efficient Way to Compute Predicted Values

       Program 8.10: Using PROC SCORE to Compute Predicted Values from a Regression Model

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