Business Statistics and Analytics in Practice: 2025 Release ISE
McGraw-Hill Education (Verlag)
978-1-265-08695-4 (ISBN)
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.
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 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 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.
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
| Erscheinungsdatum | 13.05.2025 |
|---|---|
| Verlagsort | OH |
| Sprache | englisch |
| Gewicht | 1733 g |
| Themenwelt | Mathematik / Informatik ► Mathematik |
| ISBN-10 | 1-265-08695-8 / 1265086958 |
| ISBN-13 | 978-1-265-08695-4 / 9781265086954 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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