Learn how statistical information impacts decisions in today’s business world as Camm/Cochran/Fry/Ohlmann/Anderson/Sweeney/Williams' leading STATISTICS FOR BUSINESS AND ECONOMICS, 15E connects concepts in each chapter to actual business practices. This edition combines clear statistical methods with a proven approach that presents a problem, then a scenario. Updated applications reflect the latest developments in business and statistics today. Work with more than 350 new and updated business examples, approximately 50 new and updated cases and hands-on exercises that highlight statistics in action. Gain practice using leading professional statistical software with exercises and appendices that walk you through Excel®, R and the latest JMP® Student Edition. Digital resources in WebAssign are also available to help you further strengthen your understanding of business statistics and maximize your course success.
- This edition's new learning objectives, that now appear at the beginning of each chapter, detail and explain the key concepts that are covered in each chapter. These new learning objectives are also mapped to each problem so you can easily identify which problems are addressing specific individual learning objective for focused instruction.
- Reorganized and expanded content in regression analysis and model building (ch. 16) clarifies concepts.
- Significantly expanded software support for R prepares students to use this important tool.
- Updated JMP chapter appendices reflect the most recent version of JMP statistical software.
- This edition includes more than 100 additional new problems as well as three new cases. In addition, the authors have added three new Statistic in Practice vignettes that reflect current challenges in statistics.
- Students first develop a computational foundation and master the use of techniques before moving to statistical application and interpretation of the value of techniques. Methods Exercises at the end of each section stress computation and the use of formulas, while Application Exercises require students to apply what they know about statistics to real-world problems.
- WebAssign course management solution offers a comprehensive teaching tool for business statistics.
1. Data and Statistics.
2. Descriptive Statistics: Tabular and Graphical Displays.
3. Descriptive Statistics: Numerical Measures.
4. Introduction to Probability.
5. Discrete Probability Distributions.
6. Continuous Probability Distributions.
7. Sampling and Sampling Distributions.
8. Interval Estimation.
9. Hypothesis Tests.
10. Inference about Means and Proportions with Two Populations.
11. Inferences about Population Variances.
12. Comparing Multiple Proportions, Test of Independence and Goodness of Fit.
13. Experimental Design and Analysis of Variance.
14. Simple Linear Regression.
15. Multiple Regression.
16. Regression Analysis: Model Building.
17. Time Series Analysis and Forecasting.
18. Decision Analysis
19. Nonparametric Methods.
20. Statistical Methods for Quality Control.
21. Index Numbers.
22. Sample Survey (online).
Appendix A. References and Bibliography.
Appendix B. Tables.
Appendix C. Summation Notation.
Appendix D. Microsoft Excel and Tools for Statistical Analysis.
Appendix E. Computing p-Values Using JMP and Excel.
Jeffrey D. Camm
Jeffrey D. Camm is the Inmar Presidential Chair and senior associate dean of business analytics programs in the School of Business at Wake Forest University.
James J. Cochran
James J. Cochran is associate dean for research, a professor of applied statistics and the Rogers-Spivey Faculty Fellow at The University of Alabama.
Michael J. Fry
Michael J. Fry is a professor of operations, business analytics and information systems as well as academic director of the Center for Business Analytics in the Carl H. Lindner College of Business at the University of Cincinnati.
Jeffrey W. Ohlmann
Jeffrey W. Ohlmann is associate professor of business analytics and a Huneke Research Fellow in the Tippie College of Business at the University of Iowa.
David R. Anderson
David R. Anderson is a leading author and professor emeritus of quantitative analysis in the College of Business Administration at the University of Cincinnati.
Dennis J. Sweeney
Dennis J. Sweeney is professor emeritus of quantitative analysis and founder of the Center for Productivity Improvement at the University of Cincinnati.
Thomas A. Williams
