Bruce Bowerman,
Anne M. Drougas,
William M. Duckworth
McGraw-Hill Education
10e druk, 2025
9781265086954
Business Statistics and Analytics in Practice: 2025 Release ISE
Specificaties
Paperback, blz.
|
Engels
McGraw-Hill Education |
10e druk, 2025
ISBN13: 9781265086954
Rubricering
Levertijd ongeveer 8 werkdagen
Gratis verzonden
Samenvatting
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.
Specificaties
ISBN13:9781265086954
Taal:Engels
Bindwijze:paperback
Uitgever:McGraw-Hill Education
Druk:10
Verschijningsdatum:6-3-2025
Hoofdrubriek:Wetenschap en techniek
Inhoudsopgave
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
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
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