Introduction to Statistical Reasoning

Description: Lecture, three hours; discussion, one hour; computer laboratory, two hours. Preparation: three years of high school mathematics. Not open for credit to students with credit for course 12, 13, or 15. Introduction to statistical thinking and understanding, including strengths and limitations of basic experimental designs, graphical and numerical summaries of data, inference, regression as descriptive tool. P/NP or letter grading.

Units: 5.0
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Overall Rating 3.8
Easiness 1.4/ 5
Clarity 3.6/ 5
Workload 1.6/ 5
Helpfulness 3.8/ 5
Most Helpful Review
Yeah yeah...She may make you feel like you're in an elementary school math class, but I personally liked it. Come on now... Wouldn't you rather have a professor who teaches stats to you simply or explains it in a more complicated manner?? Her practice midterm was similar to the actual midterm and she let us have a whole sheet of paper (front and back) as our cheat sheet. I would say her midterm was pretty fair, but I got a grade in the C range (with the curve!). This was because I missed a whole page of points on her midterm. I think I would have scored higher if I had paid more attention to my lecture notes and the terms she uses. Luckily, if you score higher on the final than on the midterm she'll account your final for 75% of your grade. I guess I scored much higher on the final than I did on the midterm because I ended up with an A in the class after stressing out so much over how I needed to raise my grade. Her final was alright I guess. It was open book and open notes like some other student said, but it was much different than her midterm because there were articles you had to read through. I would say about one or two of the problems on the final were confusing because I didn't know what type of answer she wanted. Just study the practice final to get some idea of the type of answers she wants from those articles. Oh and it helps if you put labeled post-it tabs in your notes and book before the final exam so you don't flip madly through your stuff trying to find the equations or examples you need. Overall I think she's an ok professor to take stats 10 with because she teaches well, but she's not easiest professor you can take it with.
Overall Rating 4.3
Easiness 4.1/ 5
Clarity 4.3/ 5
Workload 4.1/ 5
Helpfulness 4.5/ 5
Most Helpful Review
Spring 2022 - There is a reason why this professor is so highly reviewed. She was a wonderful lecturer and valued student participation. She was very sweet and understanding of students' circumstances. She was also very approachable, so if you ever have an issue, communicate with her and she will probably be able to accommodate you. Because there were so many students, it sometimes felt intimidating to speak up but the class was great nonetheless. The grade is composed of 10 online quizzes (lowest two dropped), 5 lab assignments (lowest one dropped), two exams, a final project, and extra credit. Online quizzes: These quizzes opened on Fridays and closed on Sunday nights. They were all open book and multiple choice. If you had your slides in front of you, had good notes, and understood how to work through the problem, it was not too hard to get 100%. I will admit that the quizzes did get somewhat harder towards the end of the quarter but that was to be expected. Also, if you got a bad grade on one of the quizzes, it would be dropped. I think the quizzes were really fair and I appreciated her dropping two of them. Lab: Labs were entirely guided by the TA. During lab, you learn how to code using R. Personally, I thought everything was well-paced and if I ever fell behind, I could just rewatch the lab section (my TA recorded his lab section). I also found it helpful to go to my TA’s office hours if I had any questions about the lab. From what I know, most stats 10 TAs are good at getting back to/helping students. The labs are due every two weeks and are definitely not the hardest part of this course. As a person who has never used code before, I think it wasn't too bad (especially because the TAs were so helpful). Exams: The highest scored exam is worth 30% of your grade while the second best score is worth 20% of your grade. The exams were definitely the hardest part of this course. On both exams, I only missed 4-6 questions and ended up with B’s. The exams usually consist of only 30-36 questions, so missing one can already take a toll on your grade. However, what I think really helped was having 15 pages of notes with me during the exam. The exam was not open book or open note, but she allowed you to print 15 pages (double-sided) of information to bring with you for the exam. As for any advice, I would suggest getting a reliable calculator and taking thorough notes from the slides. Even though I got two B’s, I still ended the class with a pretty good grade. Final Project: You can work in a group or you can work alone. I would suggest working in a group because, even though it is not too much work, I think it’s more efficient. The project is based on your understanding of R so getting advice from a TA would be very helpful. Extra credit: The ec can give you a 1% grade bump. You get 0.1% extra credit every time you answer a clicker question during lecture. It doesn’t have to be the right answer, you just have to show that you participated. Doing this is what bumped my grade from an A- to an A so I highly recommend doing it.
Overall Rating 3.4
Easiness 1.6/ 5
Clarity 3.6/ 5
Workload 1.4/ 5
Helpfulness 3.0/ 5
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