Elliot McClenaghan is an epidemiologist and doctoral researcher at the London School of Hygiene and Tropical Medicine, where his work focuses on the analysis of real-world health data.
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Published Content
Total: 13
Article
The One Sample T Test
In this article, we will explore some of the theory behind the one sample t test, assumptions of the test, interpretation and a worked example.
Article
The Friedman Test
The Friedman test can be used to compare repeated measures or samples, such as following a person's biological functions over time. In this article, we consider its assumptions, when to use it and go through a worked example.
Article
The Z Test
If you want to compare means of continuous variables between two groups or to a hypothesized value, you might need a z test. In this article, we explore the two types of z test, assumptions of the test, interpretation and a worked example.
Article
Pearson Correlation
In this article, we will explore the theory, assumptions and interpretation of Pearson’s correlation, including a worked example of how to calculate Pearson’s correlation coefficient, often referred to as Pearson’s r.
Article
Spearman Rank Correlation
In this article, we will explore the theory, assumptions and interpretation of Spearman’s rank correlation, a flexible statistical tool that assesses the strength and direction of the relationship between two quantitative, ranked variables.
Article
The Fisher’s Exact Test
In this article, we explore the theory, assumptions and interpretation of the Fisher’s exact test, used to investigate associations between two categorical, binary variables with small sample sizes, and take you through a worked example.
Article
An Introduction to Bayesian Statistics
Bayesian statistics has emerged as a powerful methodology for making decisions from data in the applied sciences. Bayesian brings a new way of thinking to statistics, in how it deals with probability, uncertainty and drawing inferences from an analysis.
Article
Post-Hoc Tests in Statistical Analysis
In this article, we review the function of post-hoc tests in statistical analysis, how to interpret them and when to use them (and not use them).
Article
The Wilcoxon Signed-Rank Test
The Wilcoxon signed rank test, which is also known as the Wilcoxon signed rank sum test and the Wilcoxon matched pairs test, is a non-parametric statistical test used to compare two dependent samples (in other words, two groups consisting of data points that are matched or paired). In this article, we explain how and when this test should be used.
Article
The Kruskal–Wallis Test
The Kruskal–Wallis test is a statistical test used to compare two or more groups for a continuous or discrete variable. This article explores what the Kruskal–Wallis test is, what it tells us and when it should be used.
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