Note: This review is for Fall 2020, a quarter conducted remotely for this class.

This class was Professor Vazquez's first class at UCLA. He taught this class wonderfully, combining easy-to-follow slides with examples of R code in later lectures to help us understand the application alongside the concepts. He recorded lectures and posted slides to CCLE for us to review at our leisure.

Regarding the grading scheme of the class, weights were allotted roughly equally between three categories: homework, the midterm, and the final. The homework assignments proved relatively simple and straightforward, not requiring too much time to complete. The midterm and the final had roughly similar structure: a Kaggle competition with a report (the final had a presentation component as well). These assessments were not terribly difficult; the midterm was a competition within the class, while the final was graded against thresholds set by the professor. I enjoyed the midterm and final because they more accurately resembled a situation/task we would encounter in the workplace rather than simple regurgitation of concepts and formulae.

TL;DR: Professor Vazquez teaches in a clear, easy-to-follow manner and emphasizes making our skills and knowledge relevant for the workforce, as demonstrated by the midterm and final assessments.

I really enjoyed this class! I love the way he teaches, and I learned a lot. Homeworks and exams were all super doable. I would definitely recommend this professor

I agree with all the reviews that Professor Vazquez is a good professor for his first time teaching and his class is structured well. However, one complaint I had was that this class was graded on a solid scale, meaning there aren't any +/- grades given and there isn't a curve (hopefully he'll incorporate it in his future classes). The midterm and final were Kaggle competitions that were somewhat difficult to get a high score in the model and the write-up reports were graded hard in my opinion.

*This is a review for STATS 101A, taken Winter 2022*

Professor Vazquez is really nice and funny. He breaks things down in a very easy to understand manner and is overall a fairly good professor. He outlines his class very clearly about what you will learn and you will come out of this class with a very good foundation for regression and modeling techniques. As a former stats minor (who dropped because of 100B), I do think this class was very important and interesting.

The grading, on the other hand, leaves much to be desired. The breakdown is as such: 25% Homework, 30% Midterm Exam, 30% Final Exam, and 15% Final (Group) Project. All the homeworks are done in RMarkdown and are really straightforward. It is quite easy to get 100s on all of them, just don't make silly mistakes. Grading for these is quite lenient as well. The mean on the midterm was a 73 even though the majority of the class felt they did really well. He lulls you into a false sense of security, because the exam itself is not hard if you pay attention in class and do the homeworks (pretty much exactly the same as these) - he does grade quite strictly though so you will lose points if you aren't clear. The final exam was just as "easy" although this time the class learned from their mistakes and the mean was 89. The final group project was on League of Legends - we were given a dataset of 25000 league games and were supposed to create a model to determine what factors are most important in winning gold in the game. Not that interesting imo, and he grades harshly here as well but you don't get a rubric or know what you missed out on.

Overall, grading is terrible, but you get a good foundation of regression.

I like the way Vazquez conducted the course, and I would recommend taking him if he is teaching the class. Grading consists of a homework assignment of 3-4 (+/ 2) textbook questions each week, and two equally weighted midterm and final Kaggle competition projects (which are a bit challenging, not so much because of the difficulty of the datasets but because of it being a competition within a class of so many intelligent students). The theme of his class seems to be practical application and job practice, which I appreciated. He is a clear lecturer and the way he interacted with students (especially students from abroad haha) was sweet. He records everything and attendance is not required.

Alan is a great and responsible professor. But the final project is terrible with unclear rubric and probably the grading is extremely subjective. In other words, the final project grade totally depends on luck. If you are a hard working student and aiming for an A, don’t take this class since there is no way you can decide your fate with this horrible final project.

Terrible grading scheme. This was probably one of the objectively easiest classes I've taken at UCLA, however it was also my worst grade at UCLA. Alan is nice but his grading is terrible and unfair. I feel as if I deserved way better than a B-

Didn't fully learn the material in the 100A and 100B courses so Professor Vazquez's review, simple lecture, and easy to follow slides were excellent. Always very helpful and the class is structured well. It was his first class, but definitely has the making of a great professor.

Lectures were pretty good in terms of clarity, mainly carried by the slides. However the lectures are mostly theoretical and don't really teach you how to do the homework, for that you have to solely rely on the examples done by the TA during discussion. Homeworks are weekly and seemingly short, each only having like 2-4 problems from the textbook, but they have to be done in R and you will end up writing lots of R code, so be sure to start early. The instructions in the problems are very brief and it's often not clear what exactly the professor expects you to do for each part. It's easy to miss something and lose points, but you could ask the professor on Campuswire for anything you're not sure about.

Midterm was a timed quiz on CCLE, reasonable in difficulty but also not very long, so getting a single problem wrong could greatly affect your score. No final exam, but there was instead a final project done in groups of 2 or 3 that involved planning, running, and analyzing an experiment. The final project again suffered from the same clarity issue as the homeworks and the average score was somewhere in the 70s, which would be an issue since the class isn't curved. The grade brackets were specified in the syllabus and not particularly generous.

The midterm is risky because one question wrong and you may have a different letter grade (I got above 90% for everything including the project but scuffed the midterm). The class is quite good, and I feel like I learned a lot from his R lessons. The homework is okay, though you have to write and code in R Studio (only 3 questions per week but writing in LaTex makes it long). Despite the not so good grade though I felt like learning a lot and would recommend him! Make sure to attend office hours regularly to do well in the final project.