Okay, so you wanna know about a study that totally messed up the assumptions of a statistical method? 😒 Let me tell you about this one time when I was working on a project for my stats class in grad school. We were supposed to use a t-test to compare the means of two groups, but this one group we had didn’t meet the assumptions of the test. 🤦♀️
Basically, the assumptions of a t-test are that the data are normally distributed and have equal variances. But this one group we had was super skewed and had way more variability than the other group. We tried transforming the data, but it didn’t really help. And we couldn’t just ignore the group because it was a big part of our sample. 🙄
So we ended up using a non-parametric test instead, which doesn’t assume normality or equal variances. It was a pain in the ass because we had to learn a whole new method, but at least it gave us more accurate results. 😅
Honestly, it was frustrating as hell because we had to redo a lot of our analysis and it set us back a few days. Plus, it was just annoying to have to deal with a group that didn’t fit the assumptions. But I guess that’s just how research goes sometimes. You gotta be prepared to adapt and change course when things don’t go as planned. 🤷♀️
In the end, we got our project done and it turned out pretty good. We even got a decent grade on it, which was a relief. But man, I’ll never forget that group that messed up our assumptions. 😩
