Applied linear regression for business analytics with R : a practical guide to data science with case studies
Author(s)
Bibliographic Information
Applied linear regression for business analytics with R : a practical guide to data science with case studies
（International series in operations research & management science, v. 337）
Springer, c2023
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Note
Includes bibliographical references (p. 275-276)
Description and Table of Contents
Description
Applied Linear Regression for Business Analytics with R introduces regression analysis to business students using the R programming language with a focus on illustrating and solving real-time, topical problems. Specifically, this book presents modern and relevant case studies from the business world, along with clear and concise explanations of the theory, intuition, hands-on examples, and the coding required to employ regression modeling. Each chapter includes the mathematical formulation and details of regression analysis and provides in-depth practical analysis using the R programming language.
Table of Contents
1. Introduction.- 2. Basic Statistics and Functions using R.- 3. Regression Fundamentals.- 4. Simple Linear Regression.- 5. Multiple Regression.- 6. Estimation Intervals and Analysis of Variance.- 7. Predictor Variable Transformations.- 8. Model Diagnostics.- 9. Variable Selection.
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