Monthly Archives: July 2019

Why we need to report more than “Data were analysed by t-tests or ANOVA”

T-tests and analysis of variance (ANOVA) are common statistical tests in physiology and biomedical science. While the SAMPL guidelines for reporting statistical analyses and methods in published literature state authors should “describe statistical methods with enough detail to enable a knowledgeable reader with access to the original data to verify the reported results”, such recommendations are rarely implemented. Simply stating

Read more

Python virtual environments for scientists with conda part 4

In our previous post we learned how to verify what Python virtual environments were installed on our machine and what Python packages they contained. We also learned how to delete unwanted environments. In this post we are going to learn how to share our virtual environment with others. This is incredibly useful in this day and age of research reproducibility.

Read more

Research concepts: Confidence interval of a mean

In previous posts, we learned that the aim of statistics is to extrapolate properties of samples to make inferences about population. However, random variation in individuals in the population produces sampling error, which means a single sample may not accurately reflect properties of the population. When data are binary, we learned how the 95% confidence interval (CI) of a sample

Read more

The challenge of open science for early career researchers

I assume that, if you are reading this post, you are familiar with research reproducibility and the issues that surround it. Nevertheless, you might not be familiar with the difficulties early career researchers face in this era of open science. A recent paper published in PLOS Biology by Allen & Meller entitled Open science challenges, benefits and tips in early

Read more