Statistics you are interested in: simple linear regression – part 1

We introduced simple linear regression in a previous series and learned how to perform it in R (1, 2). What is the theory behind simple linear regression? How is it used to understand relationships between variables? What is another way to perform it in Python? The hsb2.csv dataset (available here) contains demographic and academic test scores data from 200 students.

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The Open Science Framework, Part 2: adding files and contributors

In the previous post we learned how to create a project folder and pre-register a study protocol on the Open Science Framework (OSF). The OSF also serves as a good data repository to store data, and users can add contributors (i.e. collaborators) to projects. How is this done? To add files to a project, navigate to the OSF website, sign

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The Open Science Framework, Part 1: pre-registering a study protocol

Pre-registration of study protocols increases research transparency by providing a time-stamped record of experimental or analysis decisions before studies are conducted. Protocol pre-registration is now mandatory or strongly encouraged for clinical trials, and is increasingly encouraged for basic science and pre-clinical research (e.g. see the Transparency and Openness Promotion Guidelines). The Open Science Framework (OSF) is an open source software

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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

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