
SAS Statistics by Example
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Content
- Intro
- Contents
- acknow
- Chapter 1
- Introduction
- What is SAS
- Statistical Tasks Performed by SAS
- The Structure of SAS Programs
- SAS Data Sets
- SAS Display Manager
- Excel Workbooks
- Variable Types in SAS Data Sets
- Temporary versus Permanent SAS Data Sets
- Creating a SAS Data Set from Raw Data
- Data Values Separated by Delimiters
- Reading CSV Files
- Data Values in Fixed Columns
- Excel Files with Invalid SAS Variable Names
- Other Sources of Data
- Conclusions
- Chapter 2
- Introduction
- Computing Descriptive Statistics Using PROC MEANS
- Descriptive Statistics Broken Down by a Classification Variable
- Computing a 95% Confidence Interval and the Standard Error
- Producing Descriptive Statistics, Histograms, and Probability Plots
- Changing the Midpoint Values on the Histogram
- Generating a Variety of Graphical Displays of Your Data
- Displaying Multiple Box Plots for Each Value of a Categorical Variable
- Conclusions
- Chapter 3
- Introduction
- Computing Frequency Counts and Percentages
- Computing Frequencies on a Continuous Variable
- Using Formats to Group Observations
- Creating a Bar Chart Using PROC SGPLOT
- Using ODS to Send Output to Alternate Destinations
- Creating a Cross-Tabulation Table
- Changing the Order of Values in a Frequency Table
- Conclusions
- Chapter 4
- Introduction
- Producing a Simple Scatter Plot Using PROG GPLOT
- Producing a Scatter Plot Using PROC SGPLOT
- Creating Multiple Scatter Plots on a Single Page Using PROC SGSCATTER
- Conclusions
- Chapter 5
- Introduction
- Conducting a One-Sample t-test Using PROC TTEST
- Running PROC TTEST with ODS Graphics Turned On
- Conducting a One-Sample t-test Using PROC UNIVARIATE
- Testing Whether a Distribution is Normally Distributed
- Tests for Other Distributions
- Conclusions
- Chapter 6
- Introduction
- Conducting a Two-Sample t-test
- Testing the Assumptions for a t-test
- Customizing the Output from ODS Statistical Graphics
- Conducting a Paired t-test
- Assumption Violations
- Conclusions
- Chapter 7
- Introduction
- A Simple One-way Design
- Conducting Multiple Comparison Tests
- Using ODS Graphics to Produce a Diffogram
- Two-way Factorial Designs
- Analyzing Factorial Models with Significant Interactions
- Analyzing a Randomized Block Design
- Conclusions
- Chapter 8
- Introduction
- Producing Pearson Correlations
- Generating a Correlation Matrix
- Creating HTML Output with Data Tips
- Generating Spearman Nonparametric Correlations
- Running a Simple Linear Regression Model
- Using ODS Statistical Graphics to Investigate Influential Observations
- Using the Regression Equation to Do Prediction
- A More Efficient Way to Compute Predicted Values
- Conclusions
- Chapter 9
- Introduction
- Fitting Multiple Regression Models
- Producing Separate Plots Instead of a Panel
- Choosing the Best Model (Cp and Hocking's Criteria)
- Forward, Backward, and Stepwise Selection Methods
- Forcing Selected Variables into a Model
- Creating Dummy (Design) Variables for Regression
- Detecting Collinearity
- Influential Observations in Multiple Regression Models
- Conclusions
- Chapter 10
- Introduction
- Rearranging Rows and Columns in a Table
- Tables with Expected Values Less Than 5 (Fisher's Exact Test)
- Computing Chi-Square from Frequency Data
- Using a Chi-Square Macro
- A Short-Cut Method for Requesting Multiple Tables
- Computing Coefficient Kappa-A Test of Agreement
- Computing Tests for Trends
- Computing Chi-Square for One-Way Tables
- Conclusions
- Chapter 11
- Introduction
- Running a Logistic Regression Model with One Categorical Predictor Variable
- Running a Logistic Regression Model with One Continuous Predictor Variable
- Using a Format to Create a Categorical Variable from a Continuous Variable
- Using a Combination of Categorical and Continuous Variables in a Logistic Regression Model
- Running a Logistic Regression with Interactions
- Conclusions
- Chapter 12
- Introduction
- Performing a Wilcoxon Rank-Sum Test
- Performing a Wilcoxon Signed-Rank Test (for Paired Data)
- Performing a Kruskal-Wallis One-Way ANOVA
- Comparing Spread: The Ansari-Bradley Test
- Converting Data Values into Ranks
- Using PROC RANK to Group Your Data Values
- Conclusions
- Chapter 13
- Introduction
- Computing the Sample Size for an Unpaired t-Test
- Computing the Power of an Unpaired t-Test
- Computing Sample Size for an ANOVA Design
- Computing Sample Sizes (or Power) for a Difference in Two Proportions
- Using the SAS Power and Sample Size Interactive Application
- Conclusions
- Chapter 14
- Introduction
- Taking a Simple Random Sample
- Taking a Random Sample with Replacement
- Creating Replicate Samples using PROC SURVEYSELECT
- Conclusions
- References
- Index
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