From Business Statistics Made Easy in SAS. Full book available for purchase here. Chapter 1 Introduction to the Central Textbook Example...

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1 From Business Statistics Made Easy in SAS. Full book available for purchase here. Preface ix About the Author xv Acknowledgments xvii Chapter 1 Introduction to the Central Textbook Example Introduction The Company Current Research Needs of the Company Your Brief for the Case Example Extended Analytical Skills Needed in the Project 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 Introductory Case: Royal FrieslandCampina Brief Introduction to Samples, Populations & Data Basic Characteristics of Variables Chapter 4 Data Collection & Capture Introduction Correct Sampling Choose Constructs and Variable Measurements Initial Data Capture: Which Package? Dealing with Data Once It Has Been Captured

2 iv Database & Data Analysis Software Some Complications in Datasets Chapter 5 Introduction to SAS Introductory Vignette: SAS On Top of the Analytics World Brief Introduction to SAS Introduction to the Textbook Materials Getting Started with SAS 9 or SAS Studio 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.. 73 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. 84 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 Chapter 8 Basics of Associating Variables Introduction

3 v What is Statistical Association? Association Does Not Mean Causation Overview of Associations for Different Variable Types Relating Continuous or Ordinal Data: Correlation & Covariance Relating Categorical Variables Chapter 9 Using Basic Statistics to Check & Fix Data Introduction Inappropriate Data Points Dealing Practically with Missing Data Checking Centrality & Spread Strange Variable Distributions Dealing Practically with Multi-Item Scales Chapter 10 Introduction to Graphing in SAS Introduction Major Graphing Procedures in SAS The PROC SGPLOT Routine in SAS Multiple Plots Simultaneously through PROC SGPANEL Business Dashboards through PROC GKPI Geographical Mapping Using PROC GMAP PROC SGSCATTER for Multiple Scatterplots Conclusion on SAS Graphing Chapter 11 The Statistics Process: Fitting Models to Data Introduction Look for Patterns in the Data (Fit) Step 3: Interpret the Pattern Summary of the Statistics Process Chapter 12 Key Concepts: Size & Accuracy Illustrative Case: Pharmaceuticals I AstraZeneca s Crestor Introduction

4 vi Issue # 1: Size of a Statistic Issue # 2: Accuracy of Statistics The Aspects of Inaccuracy Putting Statistical Size and Accuracy Together Conclusion Appendix A to Chapter 12: More on Accuracy (optional) Chapter 13 Introduction to Linear Regression Illustrative Case: West Point Introduction The Core Textbook Case Example for Chapter 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 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

5 vii Comparing Means for More than Two Categories: ANOVA Chapter 15 Categorical Data Distributions & Associations Introduction Repeat: One-Way Categorical Distributions Repeat: Linking Categorical Variables Together Further Statistical Questions about Categorical Data Assessing One-Way Frequencies Tests of Categorical Variable Association Conclusion on Categorical Data Analysis Chapter 16 Reporting Business Analytics Reminder - Your Brief for the Textbook Case Study Your Tasks in the Analytics and Reporting Stages Background Analyses Versus Displayed Reports for the CEO Conclusion on Business Statistics Reporting 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 Introduction

6 viii Big Data Data Warehousing Machine Learning & Algorithms Simulation in Business Situations Bayesian Statistics Conclusion Chapter 19 Bibliography Books and Articles Index From Business Statistics Made Easy in SAS, by Gregory John Lee. Copyright 2015, SAS Institute Inc., Cary, North Carolina, USA. ALL RIGHTS RESERVED.

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