In the first and second posts of this series, we performed simple linear regression of a continuous outcome on a single continuous predictor, but we also learned it is possible to include binary or categorical predictors in such regression models. How is this be done? The hsb2.csv dataset we have been using also contains the variable female where male participants
Read more
In the previous post, we performed simple linear regression of science scores on reading scores from 200 students using ordinary least squares (OLS) estimation. This was done using Python’s Statsmodels package. What does the OLS output show and how should it be interpreted? Here is the figure of the individual subject data and the line of best fit, as well
Read more
Hypothesis testing vs. Estimation Hypothesis tests require that populations are Normally distributed in order for the tests to be reliable. When samples are drawn from Normally distributed populations, the distributions of F or t statistics can be calculated for any given sample size, and the F or t statistic for a specific experiment can be obtained from the distribution. This
Read more
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.
Read more
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
Read more
Linear regression is one of the most versatile tools in the data analyst’s toolbox. While it can get quite complicated, simple linear regression is rather intuitive and straightforward. In this post we will look at a small dataset so that we can work through and visualise the logic of linear regression. A bigger version of this dataset will be used
Read more