Business Statistics in Practice / Edition 4

Business Statistics in Practice / Edition 4

ISBN-10:
0072977477
ISBN-13:
9780072977479
Pub. Date:
12/09/2005
Publisher:
McGraw-Hill Companies, The
ISBN-10:
0072977477
ISBN-13:
9780072977479
Pub. Date:
12/09/2005
Publisher:
McGraw-Hill Companies, The
Business Statistics in Practice / Edition 4

Business Statistics in Practice / Edition 4

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Overview

The new edition of Business Statistics in Practice delivers clear and understandable explanations of business statistics concepts through the use of continuing case studies and an emphasis on business improvement. The cases and examples show real applications of statistics relevant to today's business students. The authors motivate students by showing persuasively how the use of statistical techniques in support of business decision-making helps to improve business processes. A variety of computer centered examples and exercises, and a robust, technology-based ancillary package are designed to help students master this subject. Acknowledging the importance of spreadsheets and statistical software in their statistical instruction, the authors continue to integrate Excel and Minitab output throughout the text. In addition, a new enhanced version of MegaStat, an Excel add-in program designed to optimize Excel for statistical application, is available free on the Student CD. For students and instructors who want to explore statistical concepts from a graphical perspective, Visual Statistics is again available on the Student CD. New Business Improvement icons are integrated throughout the text to illustrate the ‘BI’ theme.

Product Details

ISBN-13: 9780072977479
Publisher: McGraw-Hill Companies, The
Publication date: 12/09/2005
Series: The McGraw-Hill/Irwin Series Operations and Decision Sciences
Edition description: Older Edition
Pages: 912
Product dimensions: 6.00(w) x 1.25(h) x 9.00(d)

About the Author

Bruce L. Bowerman is a professor of decision sciences at Miami University in Oxford, Ohio. He received his Ph.D. degree in statistics from Iowa State University in 1974, and he has over 37 years of experience teaching basic statistics, regression analysis, time series forecasting, survey sampling, and design of experiments to both undergraduate and graduate students. In 1987 Professor Bowerman received an Outstanding Teaching award from the Miami University senior class, and in 1992 he received and Effective Educator award from the Richard T. Farmer School of Business Administration. Together with Richard T. O’Connell, Professor Bowerman has written 11 textbooks. These include Forecasting and Time Series: An Applied Approach and Forecasting, Time Series, and Regression: An Applied Approach (also coauthored with Anne B. Koehler); The first edition of Forecasting and Time Series earned an Outstanding Academic Book award from Choice magazine.

Richard T. O'Connell is an associate professor of decision sciences at Miami University in Oxford, Ohio. He has more than 32 years of experience teaching basic statistics, statistical quality control and process improvement, regression analysis, time series forecasting, and design of experiments to both undergraduate and graduate business students. In 2000 Professor O’Connell received an Effective Educator award from the Richard T. Farmer School of Business Administration. Together with Bruce L. Bowerman, he has written seven textbooks. These include Forecasting and Time Series: An Applied Approach and Linear Statistical Models: An Applied Approach. He is one of the first college instructors in the United States to integrate statistical process control and process improvement methodology into his basic business statistics course. He (with Professor Bowerman) has written several articles advocating this approach.

Table of Contents

1. An Introduction to Business Statistics

2. Descriptive Statistics

3. Probability

4. Discrete Random Variables

5. Continuous Random Variables

6. Sampling Distributions

7. Confidence Intervals

8. Hypothesis Testing

9. Statistical Inferences Based on Two Samples

10. Experimental Design and Analysis of Variance

11. Simple Linear Regression Analysis

12. Multiple Regression and Model Building

13. Time Series Forecasting

14. Process Improvement Using Control Charts

15. Nonparametric Methods

16. Chi-Square Tests

17. Decision Theory

Appendix A: Statistical Tables

Appendix B: Covariance and Correlation

Appendix C:

• Part I: Counting Rules

• Part II The Hypergeometric Distribution

Appendix D: The Normal Probability Plot

Appendix E:

• Part I: Properties of the Mean and the Variance of a Random Variable, and Covariance

Appendix F:

• Part I: Stratified Random Sampling

Answers to Most Odd-Numbered Exercises

References

Index

Appendix E: (Part 2) Derivations of the Mean and Variance of x and p On CD-ROM

Appendix F: (Part 2) Cluster Sampling and Ratio Estimation On CD-ROM

Appendix G: Using Matrix Algebra to Perform Regression Calculations On CD-ROM
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