The book has a very broad coverage, from illustrative practical examples in Regression and Analysis of Variance alongside their implementation using R, to providing comprehensive theory of the general ...

The course is an overview of Regression, and its application through R. This is a master's course. As a result, it attemps to cover both theory & practice with a depth that allows for a more than ...

In this two day course, we provide a comprehensive practical and theoretical introduction to generalized linear models using R. Generalized linear models are generalizations of linear regression ...

10.1 Kitchen sink model. We can extend the lm(y~x) function to construct a more complicated “formula” for the multi-dimensional model: lm(y ~ x1 + x2 + ... + xn ).This tells R to find the best model ...

Understanding of Linear Regression Models; Basic programming knowledge ; Simple Linear Regression. Simple linear regression is the simplest regression model of all. The model is used when there are ...

R-squared is a popular metric for measuring how well a linear regression model fits the data. It represents the proportion of variance in the response variable that is explained by the predictor ...

9.1.3 Model quality and statistical significance. We will come back to the question of whether the linear model is valid (whether it satisfies the assumptions of the technique). First we want to ...