Business Statistics, Global Edition + MyLab Statistics with eText, 4th Edition

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Business Statistics, Global Edition + MyLab Statistics with eText, 4th Edition

By Norean Sharpe, Richard De Veaux, Paul Velleman
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This pack contains 1 copy of Business Statistics, Global Edition and 1 printed access card to MyLab Statistics with eText

Business Statistics narrows the gap between theory and practice by focusing on relevant statistical methods, thus empowering business students to make good, data-driven decisions.

Using the latest GAISE (Guidelines for Assessment and Instruction in Statistics Education) report, which included extensive revisions to reflect both the evolution of technology and new wisdom on statistics education, this edition brings a modern edge to teaching business statistics. This includes a focus on the report’s key recommendations: teaching statistical thinking, focusing on conceptual understanding, integrating real data with a context and a purpose, fostering active learning, using technology to explore concepts and analyse data, and using assessments to improve and evaluate student learning. By presenting statistics in the context of real-world businesses and by emphasising analysis and understanding over computation, this book helps students be more analytical, prepares them to make better business decisions, and shows them how to effectively communicate results.

Pearson MyLab™ is the world's leading online self-study, homework, tutorial and assessment product designed with a single purpose in mind: to improve the results of all higher education students, one student at a time.

Please note: The duration of access to a MyLab is set by your instructor for your specific unit of study. To access the MyLab you need a Course ID from your instructor.


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Download a sample chapter from Business Statistics, Global Edition, 4th Edition

  • Improved organisation A streamlined design and a data-first presentation of information provides students with both the motivation to learn statistics as well as a foundation of real business decisions on which to build their statistical understanding. Chapters 5–7 now cover probability trees and Bayes’ rule. Chapter 21 is a brand-new chapter on data mining and Big Data.
  • Motivating Vignettes Each chapter opens with a vignette, which uses data from or about real-world companies, that helps students relate key statistical concepts to real business events. Companies featured include Visa, H&M, and Whole Foods Market.
  • Case Studies The book provides four cases based on realistically large datasets that challenge students to respond to accompanying open-ended business questions. These cases encourage students to bring together methods they have learned throughout the book.
  • Section Exercises Each chapter provides straightforward exercises targeted at the topics covered in each section and designed to check students’ understanding.
  • Chapter Exercises Each instance of this feature highlights a specific business or area and leads students to draw conclusions about the real world by combining concepts and methods.
Pack items
Table of 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 (
  5. Randomness and Probability (Credit Reports, the Fair Isaacs Corporation, and Equifax)
  6. Random Variables and Probability Models (Metropolitan Life Insurance Company)
  7. The Normal and Other Continuous Distributions (The NYSE)
  8. Data Sources: Observational Studies and Surveys (Roper Polls)
  9. Data Sources: Experiments (Capital One)
  10. Sampling Distributions and Confidence Intervals for Proportions (Marketing Credit Cards: The MBNA Story)
  11. Confidence Intervals for Means (Guinness & Co.)
  12. Testing Hypotheses (Casting Ingots)
  13. More About Tests and Intervals (Traveler’s Insurance)
  14.  Comparing Two Means (Visa Global Organization)
  15. Inference for Counts: Chi-Square Tests (SAC Capital)
  16. Inference for Regression (Nambé Mills)
  17. Understanding Residuals (Kellogg’s)
  18. Multiple Regression (
  19. Building Multiple Regression Models (Bolliger and Mabillard)
  20. Time Series Analysis (Whole Foods Market®)
  21. Introduction to Big Data and Data Mining (Paralyzed Veterans of America)
  22. Quality Control (Sony)
  23. Nonparametric Methods (i4cp)
  24. Decision Making and Risk (Data Description, Inc.)
  25. Analysis of Experiments and Observational Studies
Preview the detailed table of contents