Introduction to Statistical Programming with R

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.

Review Summary

Clarity
10.0 / 10
Organization
10.0 / 10
Time
10-15 hrs/week
Overall
10.0 / 10

Reviews

    Quarter Taken: Spring 2023 In-Person
    Grade: A

    This class was truly great. The professor has extremely detailed notes and basically uses that throughout the entire lecture. So if you miss his lecture, referring back to his notes will do about the same job. I still do recommend you go to his lecture as he was amazing at teaching and making sure students understood the concept. The midterm and finals were also not that hard. He allows students a cheat sheet which was extremely helpful as well. Overall, I recommend taking this class!

    Quarter Taken: Spring 2023 In-Person
    Grade: A

    I liked how organized the lectures and notes were. I still keep a copy of his notes to refer to.

    Quarter Taken: Spring 2023 In-Person
    Grade: A

    It was a good class overall. The class is easier if you have prior experience in coding but if this is the first time coding, it was still a good class.

    Quarter Taken: Fall 2023 In-Person
    Grade: A

    I like Michael Tsiang's notes. His homework was really hard but the campuswire helps a lot. His exams are also pretty hard but if you make a good cheat sheet you'll be fine.

    Quarter Taken: Fall 2023 In-Person
    Grade: A

    Mike is one of the most compassionate people I've ever met, as well as one of the most competent lecturers in the stats department. Fair curved exams, challenging but fun homework problems, and overall a highly in-depth introduction to R and RStudio that I feel anyone could benefit from.

    I had the pleasure of talking to Mike outside of class about certain questions I had pertaining to the Data Theory/Stats majors, career prospects, grad school, and the like. He discussed all that and more, taking nearly an hour out of what I imagine must be a very hectic schedule to speak to me. The most important and salient idea he imparted to me was that undergraduate education is much more than a means to getting a job. It's a flexible, enjoyable, and one-of-a-kind life situation in which you are free to explore who you are and who you wish to be, along with whatever subject matter piques your mind.

    Even if you don't enjoy coding or statistics, I'd say that this course is worth it, and even just having a chat with Mike could be greatly insightful.

    Quarter Taken: Summer 2023 In-Person
    Grade: A

    The class fell behind due to technical difficulties on day 1 which really hurt the pacing of a 6-week summer course, but Mike's lectures were very structured and methodical. The exams were extremely difficult and difficult to complete, but Mike curved the class's grades a lot. Mike was also always passionate and helpful during office hours.

    Quarter Taken: Fall 2023 In-Person
    Grade: A

    This class was very interesting, surprisingly, and Professor Tsiang clearly cares about his class, his students and the topic. His notes are incredibly organized and detailed, and I still have them saved so that I can reference them while coding in R every now and then. I also loved how this class encouraged me to think and problem-solve. I often found the homework pretty fun to do, and I really enjoyed this class much more than I originally thought I would. Professor Tsiang also implements very generous curves, and, even though you might have a rough looking raw score or below 90 on an exam, he is very considerate of the general distribution of scores. As long as you work hard and you go to lectures and discussion, do the homework (which really helps, a lot of concepts will be directly taken from homework) and try, you will get a decent grade in this class.

    Quarter Taken: Fall 2023 In-Person
    Grade: A

    I liked the structure of the lecture notes. Professor Chiang provided comprehensive pdf notes which pretty much covered everything that you need to know for the exams. Overall, very straightforward class.

Course

Instructor
Michael Tsiang
Previously taught
23F 23Su 23S 23W 22F 22Su 22S 22W 21F 21Su 21S 21W 20F 20Su 20S 20W 19F 18F 18Su 17F

Grading Information

  • No group projects

  • Attendance not required

  • 1 midterm

  • Finals week final

  • 68% recommend the textbook