- Title Page
- Copyright
- Preface
- About the Author
- Acknowledgments
- Chapter 1: Introduction to the Central Textbook Example
- Chapter 2: Introduction to the Statistics Process
- Introductory Case: Big Data in the Airline Industry
- Introduction to the Statistics Process
- Step 1: Your Needs & Requirements
- Step 2: Getting Data
- Step 3: Extracting Statistics from the Data
- Step 4: Understanding & Decision Making
- Summary: Challenges in the Statistics Process
- Advice to the Statistically Terrified
- Chapter 3: Introduction to Data
- Chapter 4: Data Collection & Capture
- Chapter 5: Introduction to SAS®
- Chapter 6: Basics of SAS Programs, Data Manipulation, Analysis & Reporting
- Introduction
- The Running Data Example
- The Pre-Analysis Data Cleaning & Preparation Steps
- Overview of the Three Big Tasks in Business Statistics
- Basic Introduction to SAS Programming
- Major Task #1: Data Manipulation in SAS
- Major Task #2: Data Analysis
- Major Task #3: SAS Reporting through Output Formats
- The Visual Programmer Mode in SAS Studio
- Conclusion
- Chapter 7: Descriptive Statistics: Understand your Data
- Introductory Case: 2007 AngloGold Ashanti Look Ahead
- Introduction
- End Outcome of a Descriptive Statistics Analysis
- Getting Descriptive Statistics in SAS
- Statistics Measuring Centrality
- Basic Statistics Assessing Variable Spread
- Assessing Shape of a Variable’s Distribution
- Conclusion on Descriptive Statistics
- Appendix A to Chapter 7: Basic Normality Statistics
- End Notes
- Chapter 8: Basics of Associating Variables
- Chapter 9: Using Basic Statistics to Check & Fix Data
- Chapter 10: Introduction to Graphing in SAS
- Chapter 11: The Statistics Process: Fitting Models to Data
- Chapter 12: Key Concepts: Size & Accuracy
- Chapter 13: Introduction to Linear Regression
- Illustrative Case: West Point
- Introduction
- The Core Textbook Case Example for Chapter 13
- Introduction to Linear Regression
- A Pictorial Walk through Regression
- Implementing Multiple Regression in SAS
- Step 1: Collect, Capture and Clean Data
- Step 2: Run an Initial Regression Analysis
- Step 3: Assess Fit and Apply Remedies If Necessary
- Step 4: Interpret the Regression Slopes
- Step 5: Reporting a Multiple Regression Result
- Other Statistical Forms
- Conclusion
- End Notes
- Chapter 14: Categories Explaining a Continuous Variable: Comparing Two Means
- Introduction to Comparison of Categories
- Features of the Continuous Variable to Compare Across Categories
- Two Types of Categories to Compare
- Numbers of Categories to Compare: Two vs. More than Two
- Data Assumptions and Alternatives when Comparing Categories
- Comparing Two Means: T-Tests
- Comparing Means for More than Two Categories: ANOVA
- End Notes
- Chapter 15: Categorical Data Distributions & Associations
- Chapter 16: Reporting Business Analytics
- Chapter 17: Business Analysis from Statistics: Introduction
- Case Study: Oracle South Africa
- Introduction
- Overall Financial Extrapolation Process
- Step 1: Statistics Gives Level of or Change in Focal Variables
- Step 2: Financial Estimates of Revenue or Cost of One Unit
- Step 3: Combine Statistics with Per-Unit Financial Values
- Step 4: Include Scope
- Steps 5 and 6: Net Profitability Calculations
- Some Simple Examples of Business Extrapolation
- Conclusion of Statistical Business Extrapolation
- Chapter 18: Miscellaneous Business Statistics Topics
- Chapter 19: Bibliography
- Index
- Additional Resources
Introduction
The final example of slightly more advanced statistics is the analysis of categorical
data, including analyses of the distributions of observations between categories as
well as associations between categories. Recall the following two sections on categorical
data from Chapters 7 and 8 as repeated next.
Last updated: April 18, 2017
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