Category Archives: Tutorials

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

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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

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Break, Continue and Pass statements using for loops in Python

In programming, for loops are used to automate repetitive tasks, such as analysing similar datasets from different subjects. Sometimes, a dataset might be slightly different to another such that the data can be used but needs to be analysed differently in the loop. For example, data might have been accidentally sampled at a higher rate, or a nested trial needs

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