Introduction to Statistical Methods for Life and Health Sciences

Lecture, three hours; discussion, one hour; laboratory, one hour. Not open for credit to students with credit for course 10, 10H, 11, 12, or 14. Presentation and interpretation of data, descriptive statistics, introduction to correlation and regression and to basic statistical inference (estimation, testing of means and proportions, ANOVA) using both bootstrap methods and parametric models. P/NP or letter grading.

Review Summary

Clarity
8.3 / 10
Organization
8.3 / 10
Time
10-15 hrs/week
Overall
8.3 / 10

Reviews

    Quarter Taken: Winter 2023 In-Person
    Grade: A

    Class has no textbook which is nice. Kim gives all the material you need to know. Lecture's are super clear, turning in your notes gives you 5% extra credit on your final grade! Only downside is all notes are hand drawn by him on a chalkboard, so you have to be there live or watch recordings to get the notes (no slides).

    Quarter Taken: Winter 2023 In-Person
    Grade: A

    super super super fair professor who goes above and beyond for his students! taught all sections, graded all work, did lectures, hosted office hours, etc. all by himself during TA strike. though lectures can seem a bit confusing they make sense when doing the homework and all material (homework, quizzes, exams) are super consistent in problem wording and difficulty

    Quarter Taken: Fall 2022 In-Person
    Grade: A+

    I really enjoyed this course! Professor Kim thoroughly explained each concept, and the content of the exams were essentially what he lectured on. My only concern going into the course was the lack of a textbook (and therefore extra practice problems) to fall back on. However, Professor Kim prepared us well for the exams, so it worked out!

    Quarter Taken: Winter 2023 In-Person
    Grade: A

    kim is a great prof and teaches really well, 100% reccomend

    Quarter Taken: Winter 2023 In-Person
    Grade: A+

    Professor is very accommodating to students' needs and teaches in an engaging format. Labs and exams are graded very fairly, recommend doing the practice hw posted.

    Quarter Taken: Winter 2023 In-Person
    Grade: A

    He's a good professor and the HW for the class isn't too time consuming or hard. The discussion section wasn't mandatory and all the coding for the lab could be easily explained by the lab manuals he posted online.

    Quarter Taken: Winter 2023 In-Person
    Grade: A+

    No textbook for the class which means no reading. The class was overall pretty easy since the midterm and final were mostly mcq. Labs were centered around coding in R which is completely different from mathlab if you took LS30 series before taking this class.

    Quarter Taken: Winter 2024 In-Person
    Grade: A

    Honestly the hardest part about this class is taking notes. The notes are super long and a lot of it is quite unnecessary but I would just do it out of respect for the Prof. Everybody loves Prof. Kim and although he strictly follows the rules he sets like no late credit or you have to label your HW perfectly he makes up for that by giving 5 percent extra credit if you turn in all your HW. Additionally, the tests are all multiple choice and you have a front and back cheat sheet which makes it pretty easy to get a full score. I missed one point off a dumb mistake, but I fully trust that with a couple hours of studying you can get a full score.

    Quarter Taken: Winter 2024 In-Person
    Grade: A

    TAKE DR. KIM! He was a very lenient professor who would always comment that the students were “running” the class and made sure that we were given enough resources to study for the midterm and final.

    Quarter Taken: Winter 2024 In-Person
    Grade: A

    super good class that is not too difficult. professor wants you to do well on exams & offers a sort of EC with the overall grade distribution of 5%. i would take this class again!

Course

Instructor
Dale Kim
Previously taught
25W 24F 24W 23F 23W 22F

Grading Information

  • No group projects

  • Attendance required

  • 2 midterms

  • Finals week final

  • 21% recommend the textbook

Previous Grades

Grade distributions not available.