Visualization & Pearson’s correlation coefficient The 30DayChartChallenge is a data visualization community that hosts daily challenges for April. Today’s challenge involves dinosaurs. I used the Datasaurus package to create an animated visualization to demonstrate the importance of graphing data, and the effects of outliers on statistical properties.

The goal of the rOpenSci Champions Program is to enable more members of historically excluded groups to participate in, benefit from, and become leaders in the R, research software engineering, and open source and open science communities. This program includes 1-on-1 mentoring for the Champions as they complete a project and perform outreach activities in their local communities.

Lissajous Curves Lissajous curves are created by plotting two oscillations on perpendicular axes and ​​​. These oscillations, represented by sinusoidal functions, intersect to create different patterns. When the ratio of these frequencies is equal to — the oscillations are equally phased— the curve is a straight line.

I’ve used Garrick Aden-Buie’s tidyexplain animations since he first made them in 2018. They’re incredibly useful for teaching—being able to see which rows left_join() includes when merging two datasets, or which cells end up where when pivoting longer or pivoting wider is so valuable.

In my causal inference class, I spend just one week talking about the Rubin causal model and potential outcomes.

TL; DR: Don’t be an absolutist– use relative paths. Use the here package instead of setwd() or getwd() to increase reproducibility and avoid wasting your and other people’s time.

RQ: What exactly is the CLT and what’s the deal with n 30? CLT - mathematical definition and simple terms definition How we use CLT How to know when empirical distribution converges to normal distribution? How did we come up with n $ $ 30? Cohen (1991) Taught that at least 30 observations were needed to use critical-ratio approach used in t-tables when comparing groups.

I’ve been working on an inherited Shiny app at work for the past few months. One of the many frustrating things about Shiny lately has been around buttons. Well, it wasn’t really about buttons, but that’s where it started. I noticed that a number of buttons - some having file inputs, some having text inputs - did not trigger every time, and I expected them to trigger every time no matter what.

Quantile Beta Regression The quantile beta regression model discussed in the 2021 paper by Running Code When you click the Render button a document will be generated that includes both content and the output of embedded code.

Throughout the Epiverse project, we use the renv R package to ensure reproducibility of the training materials and the pipelines we are providing. But we sometimes get reports from users who struggle to rebuild the environment and run the code. In this post, we dissect the source of these issues, explain why in reality renv is not at fault, and how this is caused by the inherent complexity of reproducibility.