Introduction to Business Analytics Using Simulation

Author:   Jonathan P. Pinder (School of Management, Wake Forest University, Winston-Salem NC, USA)
Publisher:   Elsevier Science & Technology
Edition:   2nd edition
ISBN:  

9780323917179


Pages:   512
Publication Date:   13 July 2022
Format:   Paperback
Availability:   Available To Order   Availability explained
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Introduction to Business Analytics Using Simulation


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Overview

Introduction to Business Analytics Using Simulation, Second Edition employs an innovative strategy to teach business analytics. The book uses simulation modeling and analysis as mechanisms to introduce and link predictive and prescriptive modeling. Because managers can't fully assess what will happen in the future, but must still make decisions, the book treats uncertainty as an essential element in decision-making. Its use of simulation gives readers a superior way of analyzing past data, understanding an uncertain future, and optimizing results to select the best decision. With its focus on uncertainty and variability, this book provides a comprehensive foundation for business analytics. Students will gain a better understanding of fundamental statistical concepts that are essential to marketing research, Six-Sigma, financial analysis, and business analytics.

Full Product Details

Author:   Jonathan P. Pinder (School of Management, Wake Forest University, Winston-Salem NC, USA)
Publisher:   Elsevier Science & Technology
Imprint:   Academic Press Inc
Edition:   2nd edition
Weight:   1.040kg
ISBN:  

9780323917179


ISBN 10:   0323917178
Pages:   512
Publication Date:   13 July 2022
Audience:   College/higher education ,  Tertiary & Higher Education
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

1. Business Analytics is Making Decisions 2. Decision Trees 3. Decision-Making and Simulation 4. Probability: Measuring Uncertainty 5. Subjective Probability Distributions 6. Empirical Probability Distributions 7. Theoretical Probability Distributions 8. Simulation Accuracy: Central Limit Theorem and Sampling 9. Simulation Fit and Significance: Chi-Square and ANOVA 10. Regression 11. Forecasting 12. Constrained Linear Optimization

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Author Information

Dr. Pinder's research has been published in Decision Sciences, the Journal of Operations Management, the Journal of Forecasting, the Journal of Economics and Business, Managerial and Decision Economics, the Journal of the Operational Research Society, Decision Sciences Journal of Innovative Education, and Decision Economics, among others. Dr. Pinder has received numerous teaching awards. He is a member of the Decision Sciences Institute and the Institute for Operations Research and Management Science.

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