Business Experiments with R - B. D. McCullough

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Résumé :
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.

Biographie:

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

Sommaire:
Preface xiii Suggested courses using this book xv Acknowledgments xix 1 Why Experiment? 1 2 Analyzing A/B Tests: Basics 49 3 Designing A/B Tests with Large Samples 107 4 Analyzing A/B Tests: Advanced Techniques 127 5 Designing Tests with Small Samples 189 6 Analyzing Designs via Regression 229 7 Two-Level Full Factorial Experiments 281 8 Two-Level Screening Designs 329 9 Custom Design of Experiments 357 10 Epilogue 397 Index 419