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- Alan Vazquez Alcocer
- STATS 101B
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*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.
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-
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.
Alan is a nice guy. however, the final project is not curved and he does not grade that easily. The instructions for the project were vague and general. My friends and I all got low grades on the project (between 70 - 75% on it) and that tanked our grades in the class.
Additionally, the midterm was multiple choice and missing one question could have an impact of a couple percentage points in your final grade in the class. One question on the midterm was the difference from a B+ and A- for me. i would go with a different professor because I think the path to a good grade would be easier / more guaranteed. however, if you are looking to learn the material, he is a great professor and he teaches with lots of enthusiasm. He knows his stuff.
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.
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.
*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.
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-
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.
Alan is a nice guy. however, the final project is not curved and he does not grade that easily. The instructions for the project were vague and general. My friends and I all got low grades on the project (between 70 - 75% on it) and that tanked our grades in the class.
Additionally, the midterm was multiple choice and missing one question could have an impact of a couple percentage points in your final grade in the class. One question on the midterm was the difference from a B+ and A- for me. i would go with a different professor because I think the path to a good grade would be easier / more guaranteed. however, if you are looking to learn the material, he is a great professor and he teaches with lots of enthusiasm. He knows his stuff.
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.
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.
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