Business Analytics

Theory and Practice
1. Auflage 2025
ISBN: 978-1-032-41557-4
Verlag: Taylor & Francis Ltd

Buch, Englisch, 400 Seiten, Format (B × H): 210 mm x 280 mm

Business Analytics is an emerging area which encompasses various technical understanding, essential for both Engineering and Management fields of study. This book presents detailed theoretical study of Business Analytics including analytical methods from various aspects such as descriptive and predictive analytics, statistical distributions, multivariate statistical analysis, time series analysis, simulation concept, optimization theory, neural network concepts, various learning techniques, visualization techniques, and performance metrics.

Features:

- Illustrates all the existing common analytics are presented in this book in significant details.

- Covers analytics, statistical concepts, multivariate statistical analysis, time series analysis, optimization, neural network, and decision analysis.

- Reviews various learning techniques, simulation, visualization techniques, and performance metrics.

- Puts emphasis on Python and R in context of business analytics.

- Includes figure-based, graphical descriptions along with numerical examples.

This book is aimed at senior undergraduate students in engineering and management including business analytics, and industrial engineering.

Zielgruppe

Academic, Postgraduate, and Undergraduate Advanced

Autoren/Hrsg.

Bandyopadhyay, Susmita

Fachgebiete

• Technische Wissenschaften Technik Allgemein Industrial Engineering

Inhaltsverzeichnis

1. Introduction

2. Discrete and Continuous Probability Distributions

3. Introduction to R Software

4. Introduction to Python and XLSTAT

5. Basic Statistics

6. Sampling and ANOVA

7. Multivariate Probability Distribution

8. Regression

9. Path Model and Discriminant Analysis

10. PCA and Factor Analysis

11. Structural Equation Modelling

12. Moving Average and Box-Jenkin’s Method

13. Time Series Models Part II

14. Mathematical Optimization Techniques

15. Dynamic Programming, Markov Analysis, and Information Theory

16. Nonlinear Optimization

17. Nature-Based Techniques and Multicriteria Decision Analysis Techniques

18. Artificial Neural Network

19. Learning Rules

20. Descriptive Analytics

21. Decision Tree

22. Other Learning Techniques

23. Simulation

24. Continuous Simulation

25. Simulation Optimization

26. Data Mining and Partitioning

27. Visualization Techniques and Dimension Reduction Techniques

28. Performance Metrics

29. Additional Techniques for Diagnostic Analytics and Prescriptive Analytics

30. Implementation of Different Methodologies with R

Über Autor(innen)

Susmita Bandyopadhyay, Ph.D. (Engineering), M.Tech. (Industrial Engineering and Management), MBA (Systems Management), MCA, B.Tech.-IT Diploma is currently serving as a Faculty member in Department of Business Administration, The University of Burdwan, West Bengal, India. This book is her fifth book. The author has published significant number of research articles in different referred International well-rated Journals and Referred International Conference Proceedings and holds almost 24 years of teaching, industrial and research experience.