Applied regression methods

This Git is part of the class of applied regression methods, examples, exercises, etc.

Description

This repository contains a large part of the exercises developed in a R Notebook. Among the exercises we find correlation exercises, Simple Linear Regression (RLS), Multiple Linear Regression (RLM), Generalized Linear Models (GLM), corresponding to the books of Daalgard (Introductory Statistics in R), and (A modern approach to regression in R) Sheater.

What I learned

• Modeling of phenomena using Simple linear regression.

• Modeling of phenomena using multiple linear regression.

  • R ^ 2
  • AIC and BIC
  • Press

• Modeling phenomena generalized linear models.

  • GLM (Binomial = ["Logit", "probit"]
  • GLM (Poisson)

• identification of significant variables.

• Identification of coefficients.

• Creation of confidence intervals.

• Validation of assumptions of the different linear models