Skip to content
New course: Interactive Dashboards with Shiny. Get 50% off with coupon SHINYLAUNCH.
R for the Rest of Us Logo

This lesson is locked

Get access to all lessons in this course.

Transcript

Click on the transcript to go to that point in the video. Please note that transcripts are auto generated and may contain minor inaccuracies.

Your Turn

  1. Perform an independent samples t-test to test whether there is a difference in exam_1 by athlete. Use var.equal = TRUE. Is there a difference? What is the p-value?

  2. Perform an independent samples t-test to test whether there is a difference in act_english by gender. Use var.equal = TRUE. Is there a difference? What is the p-value?

Notice what happens since gender has 3 levels. Try out using the filter() function from dplyr to only check the difference between Female and Male students. Alternatively, check out the page on t_test() to see how to use the comparisons argument to specify the groups to compare.

Learn More

We are using the rstatix package for the t_test() function (and other functions in later lessons). We use this package because it is tidyverse-friendly while some base R functions for inferential statistics are not. If you did want to use the base R equivalent function for a t-test, it is t.test().

Have any questions? Put them below and we will help you out!

You need to be signed-in to comment on this post. Login.