Description
Wiley Business Experiments with R by B. D. McCullough
BUSINESS EXPERIMENTS with RA unique text that simplifies experimental business design and is dedicated to the R languageBusiness 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 experimentsOffers a series of examples, focusing on a specific business questionHelps develop the ability to frame ill-defined problems and determine what data and analysis would provide information about that problemWritten 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. ABOUT THE AUTHORB. D. MCCULLOUGH, PHD, was a Professor in the Department of Decision Sciences & MIS, LeBow College of Business, Drexel University, Philadelphia, PA. TABLE OF CONTENTSPreface xiiiSuggested courses using this book xvAcknowledgments xix1 Why Experiment? 12 Analyzing A/B Tests: Basics 493 Designing A/B Tests with Large Samples 1074 Analyzing A/B Tests: Advanced Techniques 1275 Designing Tests with Small Samples 1896 Analyzing Designs via Regression 2297 Two-Level Full Factorial Experiments 2818 Two-Level Screening Designs 3299 Custom Design of Experiments 35710 Epilogue 397Index 419