Business Experiments With R

BUSINESS EXPERIMENTS with R
 
A unique text that simplifies experimental business design and is dedicated to the R language
 

Business Experiments with R offers a guide to, and explores the fundamentals of experimental business designs. The book fills a gap in the literature to provide a text on the topic of business statistics that addresses issues such as small samples, lack of normality, and data confounding. The author--a noted expert on the topic--puts the focus on the A/B tests (and their variants) that are widely used in industry, but not typically covered in business statistics textbooks.
 
The text contains the tools needed to design and analyze two-treatment experiments (i.e., A/B tests) to answer business questions. The author highlights the strategic and technical issues involved in designing experiments that will truly affect organizations. The book then builds on the foundation in Part I and expands the multivariable testing. Since today's companies are using experiments to solve a broad range of problems, Business Experiments with R is an essential resource for any business student. This important text:
* Presents the key ideas that business students need to know about experiments
* Offers a series of examples, focusing on a specific business question
* Helps develop the ability to frame ill-defined problems and determine what data and analysis would provide information about that problem
 
Written for students of general business, marketing, and business analytics, Business Experiments with R is an important text that helps to answer business questions by highlighting the strategic and technical issues involved in designing experiments that will truly affect organizations.

List of contents

Preface xiii
 
Acknowledgments xvii
 
Bruce McCullough xix
 
About the Companion Website xxi
 
1 Why Experiment? 1
 
1.1 Case: Life Expectancy and Newspapers 2
 
Exercises 6
 
1.2 Case: Credit Card Defaults 7
 
1.2.1 Lurking Variables 9
 
1.2.2 Sample Selection Bias 11
 
Exercises 13
 
1.3 Case: Salk Polio Vaccine Trials 14
 
Exercises 17
 
1.4 What Is a Business Experiment? 17
 
1.4.1 Four Steps of an Experiment 21
 
1.4.2 Big Three of Causality 22
 
1.4.3 Most Experiments Fail 23
 
Exercises 24
 
1.5 Improving Website Designs 24
 
Exercises 30
 
1.6 A Brief History of Experiments 31
 
1.7 Chapter Exercises 34
 
1.8 Learning More 34
 
1.9 Statistics Refresher 38
 
2 Analyzing A/B Tests: Basics 43
 
2.1 Case: Improving Response to Sales Calls (Two-Sample Test of Means) 44
 
2.1.1 Initial Analysis and Visualization 45
 
2.1.2 Confidence Interval for Difference Between Means 47
 
2.1.3 Reporting Results 52
 
2.1.4 Hypothesis Test for Comparing Means 52
 
2.1.5 Power and Sample Size for Tests of Difference of Means 56
 
2.1.6 Considering Costs 60
 
Exercises 62
 
2.2 Case: Email Response Test (Two-Sample Test of Proportions) 64
 
2.2.1 Confidence Interval and Hypothesis Test for Comparing Two Proportions 66
 
2.2.2 Better Confidence Intervals for Comparing Two Proportions 66
 
2.2.3 Power and Sample Size for Tests of Difference of Two Proportions 68
 
Exercises 70
 
2.3 Case: Comparing Landing Pages (Two-Sample Test of Means, Again) 71
 
Exercises 74
 
2.4 Case: Display Ad Clickthrough Rate 75
 
2.4.1 Beta-Binomial Model 75
 
2.4.2 Comparing Two Proportions Using the Beta-Binomial Model 78
 
Exercises 80
 
2.5 Case: Hotel Ad Test 81
 
2.5.1 Tips on Presenting Experimental Findings 83
 
Exercises 84
 
2.6 Chapter Exercises 84
 
2.7 Learning More 86
 
3 Designing A/B Tests with Large Samples 91
 
3.1 The Average Treatment Effect 92
 
Exercises 93
 
3.2 Internal and External Validity 93
 
3.2.1 Threats to Internal Validity 93
 
3.2.2 Threats to External Validity 95
 
Exercises 96
 
3.3 Designing Conclusive Experiments 96
 
Exercises 102
 
3.4 The Lady Tasting Tea 103
 
Exercises 103
 
3.5 Testing a New Checkout Button 104
 
Exercises 104
 
3.6 Chapter Exercises 104
 
3.7 Learning More 104
 
4 Analyzing A/B Tests: Advanced Techniques 107
 
4.1 Case: Audio/Video Test Reprise (One-Sided Tests) 108
 
4.1.1 One-Sided Confidence Intervals 109
 
4.1.2 One-Sided Power 112
 
Exercises 113
 
4.2 Case: Typing Test (Paired t-Test) 114
 
4.2.1 Matched Pairs 115
 
Exercises 119
 
4.3 A/B/n Tests 121
 
Exercises 126
 
4.4 Minimum Detectable Effect 126
 
Exercises 128
 
4.5 Subgroup Analysis 129
 
4.5.1 Deficiencies of Subgroup Analysis 132
 
4.5.2 Subgroup Analysis of Bank Data 133
 
Exercises 135
 
4.6 Simpson's Paradox 136
 
4.6.1 Sex Discrimination at UC Berkeley 137
 
4.6.2 Do You Want Kidney Stone Treatment A or Treatment B? 138
 
4.6.3 When the Subgroup Is Misleading 140
 
Exercises 143
 
4.7 Test and Roll 143
 
Exercises 145
 
4.8 Chapter Exercises 146
 
4.9 Learning More 146
 
4.

About the author

B. D. MCCULLOUGH, PHD, was a Professor in the Department of Decision Sciences & MIS, LeBow College of Business, Drexel University, Philadelphia, PA.

Summary

BUSINESS EXPERIMENTS with R

A unique text that simplifies experimental business design and is dedicated to the R language

Business Experiments with R offers a guide to, and explores the fundamentals of experimental business designs. The book fills a gap in the literature to provide a text on the topic of business statistics that addresses issues such as small samples, lack of normality, and data confounding. The author--a noted expert on the topic--puts the focus on the A/B tests (and their variants) that are widely used in industry, but not typically covered in business statistics textbooks.

The text contains the tools needed to design and analyze two-treatment experiments (i.e., A/B tests) to answer business questions. The author highlights the strategic and technical issues involved in designing experiments that will truly affect organizations. The book then builds on the foundation in Part I and expands the multivariable testing. Since today's companies are using experiments to solve a broad range of problems, Business Experiments with R is an essential resource for any business student. This important text:
* Presents the key ideas that business students need to know about experiments
* Offers a series of examples, focusing on a specific business question
* Helps develop the ability to frame ill-defined problems and determine what data and analysis would provide information about that problem

Written for students of general business, marketing, and business analytics, Business Experiments with R is an important text that helps to answer business questions by highlighting the strategic and technical issues involved in designing experiments that will truly affect organizations.

Product details

• Authors: Elea Feit, B McCullough, B D McCullough, B. D. McCullough, B. D. Feit Mccullough, Bd Mccullough
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Hardback
• Released: 30.11.2020
• EAN: 9781119689706
• ISBN: 978-1-119-68970-6
• No. of pages: 384
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Statistik, Informatik, Theorie, Data Mining, Statistics, computer science, Business & management, Wirtschaft u. Management, Data Mining Statistics, Database & Data Warehousing Technologies, Datenbanken u. Data Warehousing, Theorie der Entscheidungsfindung, Decision Sciences, R (Programm)