- 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
End Notes
1: PROC MEANS has several advantages. It allows you to stipulate the type and order
of statistics that you want. It also arranges all the variables, split by a categorical
variable, in a single table.
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Last updated: April 18, 2017
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