Member-only story
I have been studying statistics with the University of Michigan by watching the videos that they had downloaded onto YouTube. I have already watched the first video of a three video series, and the link to the review I carried out on that video can be found here:- https://tracyrenee61.medium.com/youtube-video-review-statistics-with-python-1-of-3-d44a4f8bf07f
This post is going to be comprised of a review of the second video. I have done my best to cover many key points, but one thing I would like to point out is the fact that the course providers changed datasets quite frequently. In addition, I was unable to find some of the datasets used in the course. I did, however, manage to find the cartwheel dataset, so I will provide the links for the work I have done in that regard. The course also utilised Jupyter Notebooks, but these tools were not made available in the video. I did try to make do with Google Colab whenever tutorials were conducted.
There are two types of error rates in statistics, being Type I and Type II. A type I error (false-positive) occurs if an investigator rejects a null hypothesis that is actually true in the population; a type II error (false-negative) occurs if the investigator fails to reject a null hypothesis that is actually false in the population.
