STATS 20
Introduction to Statistical Programming with R
Description: Lecture, three hours; discussion, one hour. Enforced requisite: one course from course 10, 12, 13, 15, Economics 41, or Psychology 100A, or score of 4 or higher on Advanced Placement Statistics Examination. Designed to prepare students for upper-division work in statistics. Introduction to use of R, including data management, simple programming, and statistical graphics in R. P/NP or letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Summer 2020 - Professor Lew is absolutely fantastic. Having come in with little to no programming experience (AP CS in high school), she makes learning R fun. Especially during COVID, she has been so understanding of students' struggles (e.g. recording lectures, providing opportunities for up to 10% extra credit, dropping lowest grades). Though she might seem intimidating, I would recommend anyone to attend her office hours at least once: she has so much professional experience in the stats field (i.e. not just as a professor) as well as so much wisdom to offer. This class is primarily based on projects and assignments, and unlike the other professor who teaches Stats 20, there are no formal exams. I'd say that it is very easy to earn a decent grade if you put your best foot forward; even if she were not as lenient because of the pandemic, I'd assume it'd be the same. Although I haven't received my final grade yet, I'm very confident about my performance in her class because she makes it clear how to earn points/what she's looking for (tip: don't over analyze instructions!). Some other notes: (1) there is no curve for the course, though I don't see when one would be needed and (2) don't get the recommended textbook. Because of her, I feel like I have a solid understanding of R and have decided to pursue a minor in stats! I'd love to take any future courses with her.
Summer 2020 - Professor Lew is absolutely fantastic. Having come in with little to no programming experience (AP CS in high school), she makes learning R fun. Especially during COVID, she has been so understanding of students' struggles (e.g. recording lectures, providing opportunities for up to 10% extra credit, dropping lowest grades). Though she might seem intimidating, I would recommend anyone to attend her office hours at least once: she has so much professional experience in the stats field (i.e. not just as a professor) as well as so much wisdom to offer. This class is primarily based on projects and assignments, and unlike the other professor who teaches Stats 20, there are no formal exams. I'd say that it is very easy to earn a decent grade if you put your best foot forward; even if she were not as lenient because of the pandemic, I'd assume it'd be the same. Although I haven't received my final grade yet, I'm very confident about my performance in her class because she makes it clear how to earn points/what she's looking for (tip: don't over analyze instructions!). Some other notes: (1) there is no curve for the course, though I don't see when one would be needed and (2) don't get the recommended textbook. Because of her, I feel like I have a solid understanding of R and have decided to pursue a minor in stats! I'd love to take any future courses with her.
Most Helpful Review
Winter 2026 - personally, I enjoyed this class, but I understand why others might not. if you do not have any experience whatsoever with programming, stats 20 may be a bit difficult (if you took stats 10 before this it will provide a good enough foundation IMO). take good notes in lecture and make sure you don't fall behind on homework assignments. the exams are not horrible but not easy either. take advantage of office hours and discussion to keep up. professor Maierhofer has very clear slides and is a solid lecturer. around week 7 assignments and project work begins to stack up like crazy so be prepared! a personal qualm I had with this class is the expectation to use generative AI in some later assignments (for some complicated homework problems and in the personal project). overall useful class
Winter 2026 - personally, I enjoyed this class, but I understand why others might not. if you do not have any experience whatsoever with programming, stats 20 may be a bit difficult (if you took stats 10 before this it will provide a good enough foundation IMO). take good notes in lecture and make sure you don't fall behind on homework assignments. the exams are not horrible but not easy either. take advantage of office hours and discussion to keep up. professor Maierhofer has very clear slides and is a solid lecturer. around week 7 assignments and project work begins to stack up like crazy so be prepared! a personal qualm I had with this class is the expectation to use generative AI in some later assignments (for some complicated homework problems and in the personal project). overall useful class
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