STATS 101B
Introduction to Design and Analysis of Experiment
Description: Lecture, three hours; discussion, one hour. Enforced requisite: course 101A. Fundamentals of collecting data, including components of experiments, randomization and blocking, completely randomized design and ANOVA, multiple comparisons, power and sample size, and block designs. P/NP or letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Spring 2020 - Literally the most useless professor I've ever had. Never again. He didn't tell us what the final would be like until after the P/NP deadline. Told us the format of the final 2 days before the day of the final. On top of that, doesn't reply to emails even though we're doing the entire quarter ONLINE. Unacceptable. Don't take this class with him if you can help it.
Spring 2020 - Literally the most useless professor I've ever had. Never again. He didn't tell us what the final would be like until after the P/NP deadline. Told us the format of the final 2 days before the day of the final. On top of that, doesn't reply to emails even though we're doing the entire quarter ONLINE. Unacceptable. Don't take this class with him if you can help it.
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Most Helpful Review
Spring 2022 - Shi is extremely inconsiderate and not understanding as a professor to say the least. She almost never respond to emails even with those emails addressing grading questions (she gives a one-week window for any questions related to grading and does not respond for a week, which is ridiculous). During this quarter there were still covid-related issues and concerns, Shi refused to record any live lectures even when most of the other classes still did.
Spring 2022 - Shi is extremely inconsiderate and not understanding as a professor to say the least. She almost never respond to emails even with those emails addressing grading questions (she gives a one-week window for any questions related to grading and does not respond for a week, which is ridiculous). During this quarter there were still covid-related issues and concerns, Shi refused to record any live lectures even when most of the other classes still did.
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.
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