Business Experiments with R

B. D. McCullough

• Publisher: Wiley
• Year: 2021
• ISBN:
  9781119689881
• Edition: 1
• Topic: Mathematics
• Subtopic: Probability & Statistics
• Index: Mathematics

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.

Table of contents

• Cover
• Table of Contents
• Title Page
• Copyright
• dedication
• Preface
• Acknowledgments
• Bruce McCullough
• About the Companion Website
• 1 Why Experiment?
• 2 Analyzing A/B Tests: Basics
• 3 Designing A/B Tests with Large Samples
• 4 Analyzing A/B Tests: Advanced Techniques
• 5 Designing Tests with Small Samples
• 6 Analyzing Designs via Regression
• 7 Two‐Level Full Factorial Experiments
• 8 Two‐Level Screening Designs
• 9 Custom Design of Experiments
• 10 Epilogue
• References
• Index
• End User License Agreement