Internet resource, computer file / James R. Evans.

By: James, R. Evans
Material type: TextTextPublisher: Boston: Pearson Education; 2016Edition: 2nd edDescription: 652 pISBN: 9781292095455Subject(s): Strategic planning | Business planning | Industrial management--Statistical methods | Commercial statisticsDDC classification: 658.401 Online resources: Click here to access online
Contents:
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.
Summary: Summary: A balanced and holistic approach to business analytics 'Business Analytics', 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.
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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.

Summary:
A balanced and holistic approach to business analytics 'Business Analytics', 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.

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