# Blog

### Bayesian tutorial: Two groups

The fourth of a series of tutorial posts on Bayesian analyses. In this post I focus on using brms to model the difference between two groups.

### Bayesian tutorial: Correlation

The third of a series of tutorial posts on Bayesian analyses. In this post I focus on using brms to model a correlation.

### Bayesian tutorial: Single predictor regression

The second of a series of tutorial posts on Bayesian analyses. In this post I focus on using brms to run a regression with a single predictor.

### Bayesian tutorial: Intercept-only model

The first of a series of tutorial posts on Bayesian analyses. In this post I focus on using brms to run an intercept-only regression model.

### Voting behavior of Dutch political parties on animal welfare motions

### Simulation-based power analyses

Simulation-based power analyses make it easy to understand what power is: Power is simply counting how often you find the results you expect to find. Running simulation-based power analyses might be new for some, so in this blog post I present code to simulate data for a range of different scenarios.

### The right order of method sections

Method sections in academic (psychology) papers usually consist of the following sections: Participants, Design, Procedure, and Materials. They also tend to be presented in this order. But is this, generally speaking, the right order? I don’t think so.

### Why divide by \(n - 1\) to calculate the variance of a sample?“

In a recent tweet I asked the question why we use \(n - 1\) to calculate the variance of a sample. Many people contributed an answer, but many of them were of the type I feared. Most consisted of some statistical jargon that confuses me more, rather than less. Other responses were very useful, though, so I recommend checking out the replies to the tweet. In this post, I will try to describe my favorite way of looking at the issue.

### Useful power analysis papers

A curious thing happened in the field of social psychology: Social psychologists finally realized that statistical power is important. Unfortunately, they then skipped the step of figuring out how to do them correctly. Here I list some papers on power analyses that I hope help in improving the way we do them.

### Understanding regression (part 1)

This is Part 1 of a series of blog posts on how to understand regression. The goal is to develop an intuitive understanding of the different components of regression. In this first post, we figure out where the estimate of an intercept-only regression model comes from.