## Simple linear regression in R In statistics, we often want to fit a statistical model to be able to make broader generalizations. An important type of statistical model is linear regression, where we predict the linear relationship between an outcome variable and a predictor variable. In this post we will learn how to perform a simple linear regression in R. See our previous post for

## Verify if data are normally distributed in R: part 2 In our previous post, we learned how to inspect whether or data were normally distributed or not using plots. It is always important to visualise our data. However, inspecting such plots is open for interpretation and, possibly, abuse. We will now learn how to analyse our data and generate numerical values that describe how our data are distributed. Quantifying the

## Verify if data are normally distributed in R: part 1 Many statistical tests assume that the sampling distribution is normally distributed. This does not mean that the data we collected for our experiment is normally distributed, but rather that the distribution of mean values from many samples of the same size will be normally distributed. Unfortunately, we do no have access to the sampling distribution. However, based on the central 