Overview

  For undergraduate or graduate business students.   A balanced and holistic approach to business analytics   Business Analytics, 2nd Edition teaches the fundamental concepts of the emerging field of business analytics and provides vital tools in understanding how data analysis works in today’s organisations. Students will learn to apply basic business analytics principles, communicate with analytics professionals, and effectively use and interpret analytic models to make better business decisions. Included access to commercial grade analytics software gives students real-world experience and career-focused value. Author James Evans takes a balanced, holistic approach and looks at business analytics from descriptive, and predictive perspectives.  

Full Product Details

Author:   James Evans
Publisher:   Pearson Education Limited
Imprint:   Pearson Education Limited
Edition:   2nd edition
Dimensions:   Width: 20.70cm , Height: 2.00cm , Length: 25.60cm
Weight:   1.120kg
ISBN:  

9781292095448

ISBN 10:   129209544
Pages:   656
Publication Date:   28 April 2016
Audience:   College/higher education ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

PART 1: Foundations of Business Analytics 1. Introduction to Business Analytics 2. Analytics on Spreadsheets Part 2: Descriptive Analytics 3. Visualizing and Exploring Data 4. Descriptive Statistical Measures 5. Probability Distributions and Data Modeling 6. Sampling and Estimation 7. Statistical Inference Part 3: Predictive Analytics 8. Trendlines and Regression Analysis 9. Forecasting Techniques 10. Introduction to Data Mining 11. Spreadsheet Modeling and Analysis 12. Monte Carlo Simulation and Risk Analysis Part 4: Prescriptive Analytics 13. Linear Optimization 14. Applications of Linear Optimization 15. Integer Optimization 16. Decision Analysis Supplementary Chapter A (online): Nonlinear and Non-Smooth Optimization Supplementary Chapter B (online): Optimization Models with Uncertainty Appendix A Glossary Index

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