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
Spring 2025 - I took this class as a major requirement, and it was overall ok. His lectures consisted of slides that he created and were basically just him going over his slides, going over a couple of examples on RStudio. The tests were pretty hard as he straight up made it known that his tests were made so that most people would score a 50%. His tests have an MCQ portion and a section in which you must manually write out the code, so he recommends practicing writing out code when doing your homework and such. He at least gives us access to practice midterms and finals. The TAs were amazing and held midterm/final review sessions, offered in person and through Zoom. In each section, you have a discussion assignment that you work on and go over in class that is due the next week. There were also graded quizzes that were taken on Canvas with no time limit and were open-book. My quarter was the first time he implemented a group project, one that he did not give us a good rubric for, so my group and I were pretty lost. The first time he graded it, he gave us a really low score, harshly criticizing our work, but regraded it as he admitted that he did not provide a good rubric, but said he stood by the comments he had made before. Overall, this class was stressful, but at least he grades on a curve.
Spring 2025 - I took this class as a major requirement, and it was overall ok. His lectures consisted of slides that he created and were basically just him going over his slides, going over a couple of examples on RStudio. The tests were pretty hard as he straight up made it known that his tests were made so that most people would score a 50%. His tests have an MCQ portion and a section in which you must manually write out the code, so he recommends practicing writing out code when doing your homework and such. He at least gives us access to practice midterms and finals. The TAs were amazing and held midterm/final review sessions, offered in person and through Zoom. In each section, you have a discussion assignment that you work on and go over in class that is due the next week. There were also graded quizzes that were taken on Canvas with no time limit and were open-book. My quarter was the first time he implemented a group project, one that he did not give us a good rubric for, so my group and I were pretty lost. The first time he graded it, he gave us a really low score, harshly criticizing our work, but regraded it as he admitted that he did not provide a good rubric, but said he stood by the comments he had made before. Overall, this class was stressful, but at least he grades on a curve.
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