Data science for business and decision making / Luiz Paulo Fávero, Patrícia Belfiore.
| Author/creator | Fávero, Luiz Paulo |
| Other author | Belfiore, Patrícia Prado. |
| Format | Electronic |
| Publication Info | London, United Kingdom : Academic Press, an imprint of Elsevier, [2019]. |
| Description | xvi, 1227 pages : illustrations ; 28 cm |
| Supplemental Content | Full text available from eBook - Finance 2019 |
| Subjects |
| Contents | Part 1: Foundations of Business Data Analysis -- 1. Introduction to Data Analysis and Decision Making -- 2. Type of Variables and Mensuration Scales -- Part 2: Descriptive Statistics -- 3. Univariate Descriptive Statistics -- 4. Bivariate Descriptive Statistics -- Part 3: Probabilistic Statistics -- 5. Introduction of Probability -- 6. Random Variables and Probability Distributions -- Part 4: Statistical Inference -- 7. Sampling -- 8. Estimation -- 9. Hypothesis Tests -- 10. Non-parametric Tests -- Part 5: Multivariate Exploratory Data Analysis -- 11. Cluster Analysis -- 12. Principal Components Analysis and Factorial Analysis -- Part 6: Generalized Linear Models -- 13. Simple and Multiple Regression Models -- 14. Binary and Multinomial Logistics Regression Models -- 15. Regression Models for Count Data: Poisson and Negative Binomial -- Part 7: Optimization Models and Simulation -- 16. Introduction to Optimization Models: Business Problems Formulations and Modeling -- 17. Solution of Linear Programming Problems -- 18. Network Programming -- 19. Integer Programming -- 20. Simulation and Risk Analysis Part 8: Other Topics -- 21. Design and Experimental Analysis -- 22. Statistical Process Control -- 23. Data Mining and Multilevel Modeling. |
| Abstract | Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, and IBM SPSS Statistics Software®. |
| Bibliography note | Includes bibliographical references (pages 1195-1214) and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Issued in other form | Electronic version: Fávero, Luiz Paulo. Data science for business and decision making. London, United Kingdom : Academic Press, an imprint of Elsevier, 2019 |
| Genre/form | Electronic books. |
| LCCN | 2019940509 |
| ISBN | 0128112166 paperback |
| ISBN | 9780128112168 paperback |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |