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Business Experiments with R. Edition No. 1

  • ID: 5186121
  • Book
  • May 2021
  • 384 Pages
  • John Wiley and Sons Ltd
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A unique text that simplifies experimental business design and is dedicated to the R language 

Business Experiments with R offers a guide and explores the fundamentals of experiment business designs. The book fills a gap in the literature with its discussion of business statistics, addressing 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 laid in Part I and expands on multivariable testing. Today’s companies use experiments to solve a broad range of problems, and 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 specific business questions 
  • Helps develop the ability to frame ill-defined problems and determine what data and types of analysis provide information about each problem 
  • Contains supplementary material, such as data sets available to everyone and an instructor-only companion site featuring lecture slides and an answer key  

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. 

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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

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B. D. McCullough
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