In this post we discuss how to calculate the statistical power of an expertiment using a Monte Carlo simulation in R.
We'll see how this can help refine our choice of experimental design.
R
Posts related to R
Introduction In previous posts, I discussed how to deal with situations where you measure a continuous outcome and you want to explain its variability as a function of one or more continuous or discrete variables, using linear regression or mixed-effects models. However, there are situations where these linear models are not the best solution to […]
Pseudoreplication is a major issue in biomedical sciences. This post will show you how to avoid it and properly analyse your data in R!
Binary trees are a simple, yet powerful machine learning tool used for classification. In this post, we will use them to classify images of breast cancer.
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Create awesome plots with ggplot!
This post will introduce you to ggplot, an R package which makes it super-easy to create visually pleasing plots with just a few lines of code!
Linear regression is one of the simplest, yet powerful machine learning techniques. I will teach you how to handle multiple predictors & interactions in R!
Linear regression is one of the simplest, yet extremely powerful statistical techniques, that you definitely want to study in detail. Here we will see how to do it in R!