Data science for business and decision making / Luiz Paulo Fávero, Patrícia Belfiore.

By:

Fávero, Luiz Paulo [author.]

Contributor(s):

Belfiore, Patrícia Prado [author.]

Material type: Text

TextPublication details: London : Academic Press is an imprint of Elsevier, 2019.Edition: First editionDescription: 1227 pages : illustrations ; 28 cmISBN:

0128112166
9780128112168

Subject(s):

Additional physical formats: Electronic version:: Data science for business and decision making.DDC classification:

650.01/51 F273d 2019 23

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.

Summary: 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®.

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Holdings
Item type	Current library	Call number	Copy number	Status	Barcode
Books	Premier University Business Library	650.01/51 F273d 2019	1	Available	26651
Books	Premier University Business Library	650.01/51 F273d 2019	2	Available	26652
Books	Premier University Business Library	650.01/51 F273d 2019	3	Available	26653
Books	Premier University Business Library	650.01/51 F273d 2019	4	Available	26654
Books	Premier University Business Library	650.01/51 F273d 2019	5	Available	26655

Includes bibliographical references (pages 1195-1214) and index.

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®.

BBA, MBA, EMBA.

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