Essentials of Business Statistics - Rilegato

Bruce L. Bowerman is 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 40 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 an Effective Educator award from the Richard T. Farmer School of Business Administration. Together with Richard T. OConnell, Professor Bowerman has written 16 textbooks. These include Forecasting and Time Series: An Applied Approach; Forecasting, Time Series, and Regression: An Applied Approach (also coauthored with Anne B. Koehler); and Linear Statistical Models: An Applied Approach. The fi rst edition of Forecasting and Time Series earned an Outstanding Academic Book award from Choice magazine. Professor Bowerman has also published a number of articles in applied stochastic processes, time series forecasting, and statistical education. In his spare time, Professor Bowerman enjoys watching movies and sports, playing tennis, and designing houses.

1. An Introduction to Business Statistics

2. Descriptive Statistics: Tabular and Graphical Methods

3. Descriptive Statistics: Numerical Methods

4. Probability

5. Discrete Random Variables

6. Continuous Random Variables

7. Sampling and Sampling Distributions

8. Confidence Intervals

9. Hypothesis Testing

10. Statistical Inferences Based on Two Samples

11. Experimental Design and Analysis of Variance

12. Chi-Square Tests

13. Simple Linear Regression Analysis

14. Multiple Regression and Model Building

Appendix A: Statistical Tables

Answers to Most Odd-Numbered Exercises

References

Photo Credits

Index

On the Website:

15. Process Improvement Using Control Charts

Appendix B: Properties of the Mean and the Variance of a Random Variable and the Co-variance

Appendix C: Derivatives of the Mean and Variance of x(bar) and p(hat)

Appendix D: Confidence Intervals for Parameters of Finite Populations

Appendix E: Logistic Regression