using R for analysis

in stats

September 8, 2018

I am feeling more confident about my resolution to get rid of Excel and only use R for data wrangling and visualisation. Next steps… analysis.

I’m starting simple (I presume) with t-tests. Mostly commonly I want to determine whether there is a difference in the performance of independent groups of kids, or a difference between kids' performance on two different conditions, or whether kids are just guessing (i.e. whether their performance differs significantly chance).

So I need to learn how to do:

  • independent samples t-tests
  • paired samples t-tests
  • one-sample t-tests

Where to start?

Lets see what the AMAZING Dani Navarro says about t-tests in her free online stats resources found here. If you are looking for her whole “Learning Statistics with R book” (also free) find it here.

Note: Dani also suggests looking at Matthew Crumps book “Answering questions with data” which has adapted some of her content, find it here

The functions Dani describes in her book are part of a package she wrote to accompany the book called lsr. This package includes separate commands for different kinds of t-test.

Apparently R also comes with a function t.test() that has a paired = TRUE/FALSE argument so you can specify whether you want a paired or independent samples test.

See AFL post for comparisons…

Posted on:
September 8, 2018
Length:
2 minute read, 214 words
Categories:
stats
See Also: