Statistics for Managers Using Microsoft Excel [RENTAL EDITION] (9th Edition)

Book Preface

As business statistics evolves and becomes an increasingly important part of one’s business ducation, which topics get taught and how those topics are presented becomes all the ore important. As authors, we think about these issues as we seek ways to continuously improve the quality of business statistics education. We actively participate in conferences and meetings sponsored by the Decision Sciences Institute, American Statistical Association (ASA), and INFORMS, the Institute for Operations Research and the Management Sciences. We use the ASA’s Guidelines for Assessment and Instruction (GAISE) reports and combine them with our experiences teaching business statistics to a diverse student body at several universities.

When writing a book for introductory business statistics students, four learning principles guide us.

Help students see the relevance of statistics to their own careers by using examples from the functional areas that may become their areas of specialization. Students need to learn statistics in the context of the functional areas of business. We discuss every statistical method using an example from a functional area, such as accounting, finance, management, or marketing, and explain the application of methods to specific business activities.

Emphasize interpretation and analysis of statistical results over calculation. We emphasize the interpretation of results, the evaluation of the assumptions, and the discussion of what should be done if the assumptions are violated. We believe that these activities are more important to students’ futures and will serve them better than emphasizing tedious manual calculations.

Give students ample practice in understanding how to apply statistics to business. We believe that both classroom examples and homework exercises should involve actual or realistic data, using small and large sets of data, to the extent possible.

Integrate data analysis software with statistical learning. We integrate Microsoft Excel into every statistics method that the book discusses in full. This integration illustrates how software can assist the business decision-making process. In this edition, we also integrate using Tableau into selected topics, where such integration makes best sense. (Integrating data analysis software also supports our second principle about emphasizing interpretation over calculation.)

When thinking about introductory business statistics students using data analysis software, three additional principles guide us.
Using software should model business best practices. We emphasize reusable templates and model solutions over building unaudited solutions from scratch that may contain errors. Using preconstructed and previously validated solutions not only models best practice but reflects regulatory requirements that businesses face today.

Provide detailed sets of instructions that accommodate various levels of software use and familiarity. Instruction sets should accommodate casual software users and as well as users keen to use software to a deeper level. For most topics, we present PHStat and Workbook instructions, two different sets that create identical statistical results.

Software instruction sets should be complete and contain known starting points. Vague instructions that present statements such as “Use command X” that presume students can figure out how to “get to” command X are distracting to learning. We provide instruction sets that have a known starting point, typically in the form of “open to a specific worksheet in a specific workbook.

What’s New in This Edition?

This ninth edition of Statistics for Managers Using Microsoft Excel features many passages rewritten in a more concise style that emphasize definitions as the foundation for understanding statistical concepts. In addition to changes that readers of past editions have come to expect, such as new examples and Using Statistics case scenarios and an extensive number of new endof-section or end-of-chapter problems, the edition debuts:

• Tabular Summaries that state hypothesis test and regression example results along with the conclusions that those results support now appear in Chapters 10 through 13. • Tableau Guides that explain how to use the data visualization software Tableau Public as a complement to Microsoft Excel for visualizing data and regression analysis. • A New Business Analytics Chapter (Chapter 17) that provides a complete introduction to the field of business analytics. The chapter defines terms and categories that introductory business statistics students may encounter in other courses or outside the classroom. This chapter benefits from the insights the authors have gained from teaching and lecturing about business analytics as well as research the authors have done for a forthcoming companion book on business analytics.

Content

Preface xxi
First Things First 1
1 Defining and Collecting Data 16
2 Organizing and Visualizing Variables 38
3 Numerical Descriptive Measures 108
4 Basic Probability 152
5 Discrete Probability Distributions 176
6 The Normal Distribution and Other Continuous Distributions 198
7 Sampling Distributions 224
8 Confidence Interval Estimation 244
9 Fundamentals of Hypothesis Testing: One-Sample Tests 275
10 Two-Sample Tests 311
11 Analysis of Variance 352
12 Chi-Square and Nonparametric Tests 389
13 Simple Linear Regression 430
14 Introduction to Multiple Regression 478
15 Multiple Regression Model Building 526
16 Time-Series Forecasting 556
17 Business Analytics 600
18 Getting Ready to Analyze Data in the Future 618
19 Statistical Applications in Quality Management (online) 19-1
20 Decision Making (online) 20-1
Appendices 625
Self-Test Solutions and Answers to Selected Even-Numbered Problems 673
Index 713
Credits 720