Test the heck out of your code!
One thing that surprised me was that the code itself was rarely the problem. He occasionally had some comments about the way I wrote or structured the code, but what I clearly had no idea about is testing my code.
I dreaded handing my work over to him for inspection. I slowly, painfully learned that the truly difficult part of coding is dealing with the thousands of ways things can go wrong with your application at any given time – most of them user related.
Haven't used this yet but it seems like a great idea.
Basic introduction to plotting in R (without using other packages, like ggplot2).
Now on CRAN.
Great idea from Daniel Lakens—an R script that helps you properly compare two groups.
The goal of this script is to examine whether more researcher-centered statistical tools (i.e., a one-click analysis script that checks normality assumptions, calculates effect sizes and their confidence intervals, creates good figures, calculates Bayesian and robust statistics, and writes the results section) increases the use of novel statistical procedures. Download the script here: https://github.com/Lakens/Perfect-t-test.
Looks nice!
You work through tutorials and pause to learn important concepts so that you can get into more advanced visualization. Exercises and suggested reading at the end of each week help you practice what you learn. By the end of the course, you will:
- Know how to work with real data
- Be able to explore data for analysis
- Create custom graphics fit for presentation
Jonathan Peelle, PhD
CV: PeelleCV.pdf | Google Scholar profile
Lab: peellelab.org
Office: ISEC 320
E-mail: j.peelle123@northeastern.edu(without the 123)
Mastodon: @jpeelle@neuromatch.social
("Peelle" sounds like "peel". I blame my ancestors for the extra letters.)