Professor
Alan Vazquez Alcocer
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Most Helpful Review
Winter 2022 - *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.
Winter 2022 - *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.
Most Helpful Review
Fall 2020 - 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.
Fall 2020 - 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.
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