Permalien Courriel Export
Livre imprimé
Data science for business and decision making
Auteur
Éditeur Academic Press, an imprint of Elsevier
Année 2019
Exemplaires
Notices liées
Notice détaillée
Auteur
Titre
Data science for business and decision making
Éditeur
Description
1 vol. (XVI-1227 pages) : illustrations ; 28 cm
Autre support
Fávero, Luiz Paulo. Data science for business and decision making.
Notes
Bibliogr. p. 1195-1214. Index
Collaborateurs
Sujets
Classification Dewey
650.01
Contenu
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
ISBN
0-12-811216-6
978-0-12-811216-8
Origine de la notice
Abes (SUDOC)
 

inMedia v4.4