Applied Linear Regression for Business Analytics with R A Practical Guide to Data Science with Case Studies /

Bibliographic Details
Main Author: McGibney, Daniel P. (Author)
Corporate Author: SpringerLink (Online service)
Summary:XVII, 276 p. 86 illus., 53 illus. in color.
text
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2023.
Edition:1st ed. 2023.
Series:International Series in Operations Research & Management Science, 337
Subjects:
Online Access:https://doi.org/10.1007/978-3-031-21480-6
Format: Electronic eBook
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.