Introduction For this ThuRsday Tutorial, we’re going to cover something a bit different. Instead of showing how to do fairly simple epidemiological calculations, this edition will cover the first of

Hi all, This is just a quick blog note that the ThuRsday R Tutorial will be delayed by a week (alongside the PyFriday Article) as I am writing up a

The Susceptible-Exposed-Infected-Recovered (SEIR) model is a natural extension of the SIR Model, accounting for a fourth category of disease state, Exposure. For this ThuRsday Tutorial, we’ll cover how to not

The Susceptible-Infected-Recovered (SIR) model is a fundamental concept in epidemiology, offering insights into how diseases spread and recede in populations over time through a relatively simply set of functions. For

Introduction to Relative Risk Relative Risk (RR) is one of the most fundamental measures in public health, offering insights into the strength of association between an exposure (like smoking) and

T-tests are a fundamental statistical tool used in various fields, including public health, to compare the means of two groups. Essentially, a T-test helps determine whether the observed differences in

Introduction Odds Ratio (OR) calculations are a cornerstone in public health research, providing insights into the strength of association between an exposure and an outcome. In this ThuRsday Tutorial, we’ll

Correlation is a statistical measure that describes the extent to which two variables change together. In epidemiological data analysis, understanding correlation helps in identifying relationships between variables. This tutorial

In this post, we’ll cover how to do basic Exploratory Data Analysis in R, as well as how to create some interactive visualizations.

In this article, we will cover how to read in simple CSV files into RStudio, as well as how to use R to work with more complex XSLX files.