Business Statistics, 4th edition

  • Norean R. Sharpe, 
  • Richard D. De Veaux, 
  • Paul F. Velleman

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Business Statistics helps you make solid, data-driven decisions using relevant and real-life statistical methods. With their unique blend of teaching, consulting, and entrepreneurial experiences, this distinguished author team brings a modern edge to statistics for business students. Focusing on stats in the context of real business issues and emphasizing analysis and understanding over computation, they help students become more analytical and show how to communicate results effectively. The 4th Edition's case studies, exercises and examples reflect the changing world and real-world business challenges. Vignettes present scenarios using authentic information and well-known companies such as Amazon, Zillow, Keen Inc. and Whole Foods Market to illustrate a managerial statistical issues and much more.

Published by Pearson (May 24th 2023) - Copyright © 2023

ISBN-13: 9780137897629

Subject: Advanced Statistics

Category: Introduction to Business Statistics


Brief Contents


  1. Data and Decisions (H&M)
  2. Visualizing and Describing Categorical Data (Dalia Research)
  3. Describing, Displaying, and Visualizing Quantitative Data (AIG)
  4. Correlation and Linear Regression (


  1. Randomness and Probability (Credit Reports, the Fair Isaacs Corporation, and Equifax)
  2. Random Variables and Probability Models (Metropolitan Life Insurance Company)
  3. The Normal and Other Continuous Distributions (The NYSE)


  1. Data Sources: Observational Studies and Surveys (Roper Polls)
  2. Data Sources: Experiments (Capital One)


  1. Sampling Distributions and Confidence Intervals for Proportions (Marketing Credit Cards: The MBNA Story)
  2. Confidence Intervals for Means (Guinness & Co.)
  3. Testing Hypotheses (Casting Ingots)
  4. More About Tests and Intervals (Traveler’s Insurance)
  5. Comparing Two Means (Visa Global Organization)
  6. Inference for Counts: Chi-Square Tests (SAC Capital)


  1. Inference for Regression (Nambé Mills)
  2. Understanding Residuals (Kellogg’s)
  3. Multiple Regression (
  4. Building Multiple Regression Models (Bolliger and Mabillard)
  5. Time Series Analysis (Whole Foods Market®)


  1. Introduction to Big Data and Data Mining (Paralyzed Veterans of America)


  1. Quality Control (Sony)
  2. Nonparametric Methods (i4cp)
  3. Decision Making and Risk (Data Description, Inc.)
  4. Analysis of Experiments and Observational Studies

Appendix A. Answers

Appendix B. Tables and Selected Formulas

Appendix C. Credits

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