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Business Statistics and Analytics in Practice

ISBN10: 1260253287 | ISBN13: 9781260253283

Business Statistics and Analytics in Practice
ISBN10: 1260253287
ISBN13: 9781260253283
By Bruce Bowerman, Anne M. Drougas and William M. Duckworth

* The estimated amount of time this product will be on the market is based on a number of factors, including faculty input to instructional design and the prior revision cycle and updates to academic research-which typically results in a revision cycle ranging from every two to four years for this product. Pricing subject to change at any time.

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The 2025 release of Business Statistics and Analytics in Practice offers a comprehensive approach to teaching business statistics and analytics. It covers essential topics like probability modeling, regression, and time series, while seamlessly integrating modern tools such as data mining and
predictive analytics. Real-world case studies and early introductions to advanced visualizations enhance practical learning, with Business Improvement conclusions-highlighted
in yellow and marked by BI icons-demonstrating how statistical analyses lead to actionable business decisions. With
hands-on experience using Excel, MegaStat, Minitab, JMP, and R, students are equipped with the skills needed to thrive in today’s data-driven business world.

1.  An Introduction to Business Statistics and Analytics 
2.  Descriptive Statistics and Analytics: Tabular and Graphical Methods 
3.  Descriptive Statistics and Analytics: Numerical Method
4.  Probability and Probability Models
5.  Predictive Analytics I: Trees, k-Nearest Neighbors, Naive Bayes’, and Ensemble Estimates 
6.  Discrete Random Variables 
7.  Continuous Random Variables 
8.  Sampling Distributions 
9.  Confidence Intervals 
10. Hypothesis Testing 
11. Statistical Inferences Based on Two Samples 
12. Experimental Design and Analysis of Variance 
13. Chi-Square Tests 
14. Simple Linear Regression Analysis 
15. Multiple Regression and Model Building 
16. Predictive Analytics II: Logistic Regression, Discriminate Analysis, and Neural Networks 
17. Time Series Forecasting and Index Numbers 
18. Nonparametric Methods 
19. Decision Theory 
20. (Online) Process Improvement Using Control Charts for Website 

Appendix A: Statistical Tables 
Appendix B: (Online) Chapter by Chapter MegaStat Appendices

About the Author

Bruce Bowerman

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. O’Connell, 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.

Anne M. Drougas

Anne M. Drougas is a Professor of Finance and Quantitative Methods at Dominican University in River Forest, Illinois. Over the course of her academic career, she has received three teaching awards and has developed and taught online and hybrid business statistics and finance courses. Her research is primarily in the areas of corporate finance, simulation, and business analytics with publications in a number of journals including the Journal of Financial Education and Journal of Applied Business and Economics. She spends her spare time with her family and serving on the board of directors for Hephzibah House, a social service agency for children in Oak Park, Illinois.

William M. Duckworth

William M. Duckworth specializes in statistics education and business applications of statistics. His professional affiliations have included the American Statistical Association (ASA), the International Association for Statistical Education (IASE), and the Decision Sciences Institute (DSI). Dr. Duckworth was also a member of the Undergraduate Statistics Education Initiative (USEI), which developed curriculum guidelines for undergraduate programs in statistical science that were officially adopted by the ASA. Dr. Duckworth has published research papers, been an invited speaker at professional meetings, and taught company training workshops, in addition to providing consulting and expert witness services to a variety of companies. During his tenure in the Department of Statistics at Iowa State University, his main responsibility was coordinating, teaching, and improving introductory business statistics courses. Dr. Duckworth currently teaches business analytics to both undergraduate and graduate students in the Heider College of Business at Creighton University.

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