Jingchen Liu

Hard Hard Hard. This class will existentially try an love you have for probability. There are grad students in the class so I think it somewhat prevents the curve from falling too low. Prof Liu in lecture is not the clearest of lecturers. He has an accent, but the biggest detriment to his lectures is the fact that he has a habit of whispering and writing very lightly on the board. On the first day of class someone asked if he could speak up, and he said, "how about you move up?" The midterm was actually fairly doable, aside from one question that our TA, a PhD student had gotten stuck on while trying the exam and one that took about two blackboards to do when he gave us the solutions later. The final was fairly hard, with the median score at about a 50, which considering the fact that a large proportion of the class is try-hard masters students is pretty bad. I saw the person in front of me dolefully regret their choice to complete the exam in pen. That being said though, Professor Liu is a genius and the TA was absolutely great. Statistics beyond the introductory level is hard anyway, so this probably (no pun intended) is the good kick in the head we all need anyway.

I learned about probability distributions and theorems.

Simple linear models. Multiple linear models. ANOVA. Hypothesis testing ...

a little bit of everything - linear regression, glm, optimization

Worst Prof ever. Couldn't be bothered to attend half of office hours throughout the semester, couldn't teach well, didn't have an organized syllabus, and drafted a final exam that reflect almost zero knowledge of whatever was taught in the semester. Avoid him at all costs.

all the linear regression stuff, i never thought it would be so much like this

Linear regression, nonparametric methods, MCMC

axioms of probability, conditional probability, expectations, continuous and discrete random variables, bayes

Linear Regression (including ANOVA): point estimation, interval estimation, hypothesis testing; Model selection (AIC, BIC, etc.); other models like random effects, logistic/LDA, etc. Some data analysis techniques (transformations, etc.)

这门课若不是必选，作为一个统计学硕士阶段的课程纯属骗钱 1 Columbia University: Arts & Sciences Spring 2025 Course: STATGR5203_001_2025_1-PROBABILITY : STATGR5203_001_2025_1 - PROBABILITY Instructor: Jingchen Liu