Terrible class, and meyer was unfortunately very unclear and unhelpful. Seems like a nice enough guy, but just had no good structure or idea how to teach concepts effectively. The concepts were disjoint, random, and not useful to anything we have done or need to do later. Also why is it in python if we only have to learn C++, but we never learn how to do any of the code, he just gives us complex problems.

This class is incredibly useful if you are interested in research, but also incredibly frustrating because of the homeworks.

The class follows a structure where a statistical concept or model will be introduced in lecture and then you will implement that model using python in the following week's homework. The implementation of the model is based on a bioengineering paper, so if the authors did linear regression, then you will perform the same linear regression with the author's data. In theory, this is a great way to show how statistics is used in research and teaches you exactly how you might come to a certain conclusion with data you collected. But in practice the homework questions are often vaguely worded, so you don't know exactly what is expected of you and you don't know what your results are supposed to look like. This led to the homeworks taking (me) upwards of 8 hours to complete. However, Meyer and the TAs are VERY helpful in clarifying what the questions are asking for and what you should be looking for in the final result. For the love of god, I cannot stress this enough: go to office hours every single week. Every 10 minutes spent in office hours saves you an hour of frustration. If you have any exposure to coding, then python is a very simple language to learn and not the main obstacle when it comes to doing the homework.

The grading scheme was:
Final Project (30%)
Midterm (30%)
Homework Assignments (20%)
Class Participation (20%)

Our year's midterm was hard (supposedly the hardest in the history of the class according to the TA), but it is about half easy-memorization questions and half hard-application-of-statistics-equations questions.

The final project is a group project where your group has to come up with a novel data analysis of some biology related data set (although it doesn't have to be biology related, a couple groups did analyses on video games such as pokemon and super smash bros). The difficulty of this depends a lot on what kind of model you decide to implement and the data that you are using. If the dataset is poorly formatted, then a lot of your time might get sucked into reformatting it. If your model is finicky, then you might not get any conclusive results (which is perfectly fine).

Class participation is mainly just general class participation and getting feedback on project proposals before submitting, so this should be a free 20%.