Learn how to run multiple comparison tests in Excel and R to pinpoint mean differences in multiple groups of data.
- [Conrad] Compare Group A with Group B to find out if there's a significant difference in their means. Okay, that's a fairly simple task. Now do the same thing with groups A, B, and C. All right, not much more difficult. Now, figure out which groups have caused one or more significant differences. Aha, that requires a lot more thought. Sometimes statistical analysis isn't as easy as just running a T test or ANOVA and interpreting the results. In the scenario that I just presented, you have to use something called multiple comparison tests. Don't know what those are? Don't worry, that's where I can help. My name is Conrad Carlberg. I've spent a long time reading, writing, and doing statistical analysis. In this particular course, I'm going to show you how to use the Tukey HSD and Scheffe multiple comparison tests to run an analysis following an ANOVA. The end results will show you which groups bring about significant mean differences. I'll talk with you a bit about critical values, group sizes, flexibility, and power, and how those criteria guide your choice of tests. In order to run the analysis, I'll be using Microsoft Excel and the open source platform R. If you want to follow along, you should have those two applications installed on your machine. We'll spend some time comparing results from the two software packages along the way. Enough introduction, let's dive right into multiple comparison testing using Excel and R.