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In Statistics for Business: Decision Making and Analysis, authors Robert Stine and Dean Foster of the University of Pennsylvania’s Wharton School, take a sophisticated approach to teaching statistics in the context of making good business decisions. The authors show students how to recognize and understand each business question, use statistical tools to do the analysis, and how to communicate their results clearly and concisely.

In addition to providing cases and real data to demonstrate real business situations, this text provides resources to support understanding and engagement. A successful problem-solving framework in the 4-M Examples (Motivation, Method, Mechanics, Message) model a clear outline for solving problems, new What Do You Think questions give students an opportunity to stop and check their understanding as they read, and new learning objectives guide students through each chapter and help them to review major goals. Software Hints provide instructions for using the most up-to-date technology packages. The Second Edition also includes expanded coverage and instruction of Excel^® 2010 and the XLSTAT^™ add-in.

The MyStatLab^™ course management system includes increased exercise coverage with the Second Edition, along with 100% of the You Do It exercises and a library of 1,000 Conceptual Questions that require students to apply their statistical understanding to conceptual business scenarios. Business Insight Videos show students how statistical methods are used by real businesses, and new StatTalk Videos present statistical concepts through a series of fun, brief, real-world examples. Technology tutorial videos at the exercise level support software use.

Statistics for Business: Pearson New International Edition

• Table of Contents


• 1. Introduction


• 2. Data


• 3. Describing Categorical Data


• 4. Describing Numerical Data


• 5. Association between Categorical Variables


• 6. Association between Quantitative Variables


• 7. Probability


• 8. Conditional Probability


• 9. Random Variables


• 10. Association between Random Variables


• 11. Probability Models for Counts


• 12. The Normal Probability Model


• 13. Samples and Surveys


• 14. Sampling Variation and Quality


• 15. Confidence Intervals


• 16. Statistical Tests


• 17. Comparison


• 18. Inference for Counts


• 19. Linear Patterns


• 20. Curved Patterns


• 21. The Simple Regression Model


• 22. Regression Diagnostics


• 23. Multiple Regression


• 24. Building Regression Models


• 25. Categorical Explanatory Variables


• 26. Analysis of Variance


• 27. Time Series


• 28. Alternative Approaches to Inference


• 29. Regression with Big Data


• 30. Two-Way Analysis of Variance


• Index


• A


• B


• C


• D


• E


• F


• G


• H


• I


• J


• K


• L


• M


• N


• O


• P


• Q


• R


• S


• T


• U


• V


• W


• Y


• Z