Data Science for Business and Decision Making
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Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
Not in stock at Prospero.
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Product details:
- Publisher Elsevier Science
- Date of Publication 3 June 2019
- ISBN 9780128112168
- Binding Paperback
- No. of pages1244 pages
- Size 276x215 mm
- Weight 2450 g
- Language English 0
Categories
Long description:
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 Softwareï¿1⁄2, and IBM SPSS Statistics Softwareï¿1⁄2.
MoreTable of 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
