A Gentle Introduction to Statistics Using SAS Studio (Hardcover edition)

274 Pages·2019·10.929 MB·English

by  Ron Cody

Contents
1. About This Book
1. What Does This Book Cover?
2. Is This Book for You?
3. What Should You Know about the Examples?
1. Example Code and Data
2. SAS University Edition
4. Where Are the Exercise Solutions?
5. We Want to Hear from You
2. About The Author
3. Acknowledgments
4. Chapter 1: Descriptive and Inferential Statistics
1. Overview
2. Descriptive Statistics
3. Inferential Statistics
4. Summary of Statistical Terms
5. Chapter 2: Study Designs
1. Introduction
2. Double-Blind, Placebo-Controlled Clinical Trials
3. Cohort Studies
4. Case-Control Studies
5. Conclusion
6. Chapter 3: What Is SAS University Edition?
1. Introduction
2. How to Download SAS University Edition
3. Conclusion
7. Chapter 4: SAS Studio Tasks
1. Introduction
2. Using the Built-in Tasks
3. Taking a Tour of the Navigation Pane
4. Exploring the LIBRARIES Tab
5. Conclusion
8. Chapter 5: Importing Data into SAS
1. Introduction
2. Exploring the Utilities Tab
3. Importing Data from an Excel Workbook
4. Listing the SAS Data Set
5. Importing an Excel Workbook with Invalid SAS
Variable Names
6. Importing an Excel Workbook That Does Not
Have Column Headings
7. Importing Data from a CSV File
8. Shared Folders (Accessing Data from Anywhere
on Your Hard Drive)
9. Conclusion
9. Chapter 6: Descriptive Statistics – Univariate Analysis
1. Introduction
2. Generating Descriptive Statistics for Continuous
Variables
3. Investigating the Distribution of Horsepower
4. Adding a Classification Variable in the Summary
Statistics Tab
1. Computing Frequencies for Categorical
Variables
5. Creating a Filter Within a Task
6. Creating a Box Plot
7. Conclusion
8. Chapter 6 Exercises
10. Chapter 7: One-Sample Tests
1. Introduction
2. Getting an Intuitive Feel for a One-Sample t Test
3. Performing a One-Sample t Test
4. Nonparametric One-Sample Tests
5. Conclusion
6. Chapter 7 Exercises
11. Chapter 8: Two-Sample Tests
1. Introduction
2. Getting an Intuitive Feel for a Two-Way t Test
3. Unpaired t Test (t Test for Independent Groups)
4. Describing a Two-Sample t Test
5. Nonparametric Two-Sample Tests
6. Paired t Test
7. Conclusion
8. Chapter 8 Exercises
12. Chapter 9: Comparing More Than Two Means (ANOVA)
1. Introduction
2. Getting an Intuitive Feel for a One-Way ANOVA
3. Performing a One-Way Analysis of Variance
4. Performing More Diagnostic Plots
5. Performing a Nonparametric One-Way Test
6. Conclusion
7. Chapter 9 Exercises
13. Chapter 10: N-Way ANOVA
1. Introduction
2. Performing a Two-Way Analysis of Variance
3. Reviewing the Diagnostic Plots
4. Interpreting Models with Significant Interactions
5. Investigating the Interaction
6. Conclusion
7. Chapter 10 Exercises
14. Chapter 11: Correlation
1. Introduction
2. Using the Statistics Correlation Task
3. Generating Correlation and Scatter Plot Matrices
4. Correlations among Variables in the Fish Data
Set
5. Interpreting Correlation Coefficients
6. Generating Spearman Non-Parametric
Correlations
7. Conclusion
8. Chapter 11 Exercises
15. Chapter 12: Simple and Multiple Regression
1. Introduction
2. Getting an Intuitive Feel for Regression
3. Describing Simple Linear Regression
4. Understanding How the F Value Is Computed
5. Investigating the Distribution of the Residuals
6. Measures of Influence
7. Demonstrating Multiple Regression
8. Running a Simple Linear Regression Model with
Endurance and Pushups
9. Demonstrating the Effect of Multi-Collinearity
10. Demonstrating Selection Methods
11. Using a Categorical Variable as a Predictor in
Model
12. Conclusion
13. Chapter 12 Exercises
16. Chapter 13: Binary Logistic Regression
1. Introduction
2. Describing the Risk Data Set
3. Running a Binary Logistic Regression Model
with a Single Predictor Variable
4. A Discussion about Odds Ratios
5. Editing SAS Studio-Generated Code
6. Using a Continuous Variable as a Predictor in a
Logistic Model
7. Running a Model with Three Classification
Variables
8. Conclusion
9. Chapter 13 Exercises
17. Chapter 14: Analyzing Categorical Data
1. Introduction
2. Describing the Salary Data Set
3. Computing One-Way Frequencies
4. Creating Formats
5. Producing One-Way Tables with Formats
6. Reviewing Relative Risk, Odds Ratios, and Study
Designs
7. Creating Two-Way Tables
8. Using Formats to Reorder the Rows and Columns
of a Table
9. Computing Chi-Square from Frequency Data
10. Analyzing Tables with Low Expected Values
11. Conclusion
12. Chapter 14 Exercises
18. Chapter 15: Computing Power and Sample Size
1. Introduction
2. Computing Sample Size for a t Test
3. Calculating the Sample Size for a Test of
Proportions
4. Computing Sample Size for a One-Way ANOVA
Design
5. Conclusion
6. Chapter 15 Exercises
19. Odd-Numbered Exercise Solutions
1. Chapter 6 Solutions
2. Chapter 7 Solutions
3. Chapter 8 Solutions
4. Chapter 9 Solutions
5. Chapter 10 Solutions
6. Chapter 11 Solutions
7. Chapter 12 Solutions
8. Chapter 13 Solutions