Applied Linear Regression for Business Analytics with R : A Practical Guide to Data Science with Case Studies / by Daniel P McGibney
Por: McGibney, Daniel P, autor
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Tipo de material: 
E-bookSeries (International Series in Operations Research & Management Science, 2214-7934 ;; 337).Editor: Cham : Springer International Publishing, 2023Edición: 1st ed 2023.Descripción: 1 recurso en línea.ISBN: 9783031214806.Tema: Análisis de sistemasRecursos en línea: Acceso a este recurso digital (usuarios Universidad Europea de Valencia)
| Tipo de ítem | Biblioteca actual | Signatura topográfica | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems | |
|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
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Valencia Digital Acceso Electrónico (UEV) | T57.6 2023 EB (Navegar estantería(Abre debajo)) | Acceso electrónico | eBook16022374 |
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.
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.
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