| Edition |
1st ed. 2023. |
| Descript. |
XVII, 276 pages 86 illustrations, 53 illustrations in color. online resource. |
| Phys Desc |
text file PDF rda |
| Series |
International Series in Operations Research & Management Science,
2214-7934 ; 337
|
|
International Series in Operations Research & Management Science, 2214-7934 ; 337
|
| 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. |
| Summary |
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. |
| Sys Details |
eBook access requires you to log in as a Federation University Australia library user |
| Notes |
Springer Nature eBook |
| Subject |
Operations research.
|
|
Regression analysis.
|
|
Business information services.
|
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Business -- Data processing.
|
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Mathematical statistics -- Data processing.
|
| Other Author |
SpringerLink (Online service)
|
| ISBN |
9783031214806 |
| ISBN/ISSN |
10.1007/978-3-031-21480-6 doi |
|
