MATH 170E
Introduction to Probability and Statistics 1: Probability
Description: Lecture, three hours; discussion, one hour. Requisite: course 32B. Highly recommended: course 61 or 70. Not open to students with credit for course 170A, Electrical and Computer Engineering 131A, or Statistics 100A. Introduction to probability theory with emphasis on topics relevant to applications. Topics include discrete (binomial, Poisson, etc.) and continuous (exponential, gamma, chi-square, normal) distributions, bivariate distributions, distributions of functions of random variables (including moment generating functions and central limit theorem). P/NP or letter grading.
Units: 4.0
Units: 4.0
3 of 4
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Most Helpful Review
Spring 2024 - Combinatorics does not come naturally to me and I found even the basics confusing. Things eventually clicked in how to recognize certain simpler distributions for the homework problems, but Professor Needell wasn't particularly helpful in this. I did not learn much in class, and I had to watch learn via looking up solutions. I have no idea how to recognize or the real world applications of half of the distributions we learned about (ex. Gamma, Chi-Square), which is disappointing since I know they are used quite extensively in multiple fields of study. There was a tedious-amount of homework, which I guess were helpful in tackling exam problems, since I did not learn much from lectures. I can't speak to how helpful she is outside of class (because I never figured out her office hours sign up). Her first two exams were relatively-easy in regard to the content we were learning, but the final was very hard. I was saved by the fact that it was multiple-choice and made very good educated guesses. In summary, I think that there must be better 170E professors than Needell, since I didn't learn much directly from her, but I don't think this class is necessarily that difficult.
Spring 2024 - Combinatorics does not come naturally to me and I found even the basics confusing. Things eventually clicked in how to recognize certain simpler distributions for the homework problems, but Professor Needell wasn't particularly helpful in this. I did not learn much in class, and I had to watch learn via looking up solutions. I have no idea how to recognize or the real world applications of half of the distributions we learned about (ex. Gamma, Chi-Square), which is disappointing since I know they are used quite extensively in multiple fields of study. There was a tedious-amount of homework, which I guess were helpful in tackling exam problems, since I did not learn much from lectures. I can't speak to how helpful she is outside of class (because I never figured out her office hours sign up). Her first two exams were relatively-easy in regard to the content we were learning, but the final was very hard. I was saved by the fact that it was multiple-choice and made very good educated guesses. In summary, I think that there must be better 170E professors than Needell, since I didn't learn much directly from her, but I don't think this class is necessarily that difficult.
Most Helpful Review
Spring 2021 - Maybe I'm the stupid one in the class as everyone in the class gets like As on their tests. Not the best lecturer, but also not the worse. The test are extremely long and definitely not 3 hours for the finals. The class is not curved so keep that in mind (45% midterm, 25% hw, 35% finals). I just pnp the class cuz I know I will not learn anything from the class. Take it with another professor if you can.
Spring 2021 - Maybe I'm the stupid one in the class as everyone in the class gets like As on their tests. Not the best lecturer, but also not the worse. The test are extremely long and definitely not 3 hours for the finals. The class is not curved so keep that in mind (45% midterm, 25% hw, 35% finals). I just pnp the class cuz I know I will not learn anything from the class. Take it with another professor if you can.
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Winter 2022 - Professor Pedchenko is my favorite professor at UCLA so far. He gives really clear lectures and none of them are boring. He really cares about students, often listening to student feedback via an anonymous survey that he checks every week. He also provides concise lecture notes after every class, uploading them to Canvas. His homeworks are also very fair and if you have trouble he will go over it with you during office hours. All in all I would recommend Pedchenko!!
Winter 2022 - Professor Pedchenko is my favorite professor at UCLA so far. He gives really clear lectures and none of them are boring. He really cares about students, often listening to student feedback via an anonymous survey that he checks every week. He also provides concise lecture notes after every class, uploading them to Canvas. His homeworks are also very fair and if you have trouble he will go over it with you during office hours. All in all I would recommend Pedchenko!!
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