Amazing professor and amazing class! Professor Cha lectures really well and cares for her students. The grading scheme is also very fair. Highly recommend this professor!

Despite being uncannily clear, the lecturer (not a professor) fumbled with the languages as she only knew R. Hence, there was no way for Ms. Cha to teach SAS/STATA/SPSS

Homework assignments were really helpful for learning the content. Exams were generally easier than the homework questions as well. Slides were easy to understand and she provided practice exams for both exams. Overall would recommend taking this class with Professor Cha as I genuinely feel like I learned a lot and really enjoyed it!

I have already take AP Statistics and scored a 5 on the exam but as a Statistics and Data Science major we were required to retake Stats 10, so take my review with a grain of salt. Professor Cha was a very kind a funny professor who clearly cared about her students. Lecture attendance was not mandatory, but for every lecture you attended you would get 0.1% extra credit on your final grade (maxing out at 10 lecture for 1% extra credit). Discussion attendance was also optional but I highly recommend going. Lectures were recorded and annotated slides were posted so I rarely went to lectures by the end of the quarter because I already knew most of the information being taught. The only aspect of coding you have to do is the R studio coding apart of the Lab grade but the TAs basically give you all the answers during discussion. My TA shared her screen and we just copied what she typed. There is also a final project that is coding based but it is very straightforward. The exams are very similar to the quizzes and practice exams she posts so they are not that difficult. The exams are also not cumulative.
The grading scheme is:
15% - takehome canvas quizzes - lowest two quizzes get dropped
20% - Labs (coding) - lowest grade gets dropped
20% - lowest of the two exams
30% - highest of the two exams
15% - final group project
1% Extra Credit - Lecture attendance

Grade Division:
- Online Quizzes - 15%
This class had almost weekly online quizzes which were about the material learned during the week. The formatting included multiple choice, drop down questions, and short response with only one attempt allowed per quiz but no time limit. No late submissions were accepted since the quizzes open on Friday morning and close on Sunday night which should be enough time to complete them. I think the quizzes were pretty easy as long as the lecture was making sense to me.
- Labs - 20%
You have two weeks to work on each lab. TA's walk you through the labs during discussion. The labs use R Studio and involve coding which TA's will guide you through. They are due on Saturday at 11pm and are deducted by 10% for every day last before the hard deadline on Monday. The lowest lab is dropped. I think the labs were pretty easy overall as long as I was attending my discussion section because my TA would go over everything pretty thoroughly.
- Exams - 20 and 30% (50% total)
Both the midterm and final exam are in person and require Respondus Lockdown to be completed. You have 70 mins (all of class time) to complete these exams. The final is not cumulative. Whichever exam you score higher on ends up weighing more in your final grade. There is no coding included in these exams. If I had studied more for these exams then I probably would have done better in the overall course. Personally I did better on the midterm than the final mainly because during the last five weeks she had a couple online lectures during the fall quarter and that totally threw me off. Otherwise I probably would have done better.
- Group Project - 15%
This project requires collaboration with other classmates either your own group or a randomly selected group of up to 7 people. Project is due towards the end of the quarter. The professor and the TA's provide assistance for the project.
- Extra Credit - 1%
Given for participation during lectures by answering iclicker questions. Answers do not have to be correct.

Professor:
Overall I think Professor Cha was clear and concise. She provided resources such as the optional textbook and her annotated slides which detail the textbook chapter by chapter. Despite her having some strict deadlines she does provide opportunities to improve your grade which I think is always a plus. She remained focused and made sure to address any questions that came up during lectures. As long as you get everything done in a timely manner and reach out to her and/or your TA for help you should be okay.

Notes:
- There is a textbook for this class and it is optional, I'm pretty sure it is also available online so I would recommend to opt out of it at the beginning of the quarter.
- Grades are not curved unless she sees that the majority of the class is not doing well (stated in her syllabus)
- She records her lectures and posts the slides but you will not receive extra credit if you never show up because the iclicker tracks your location.
- This course requires the usage of a laptop to complete the labs and the exams.
- R and RStudio are required software
- A cheat sheet was allowed for exams but I would still highly recommend that you study beforehand so you really get an understanding of what you've learned.
- Coding is not a part of any of the exams or quizzes but it IS included in the labs and the group project.

if you took ap stats in high school and did well this class will be incredibly easy. if not it’s still pretty easy to follow along! the weekly quizzes were open book and very easy. i was mostly worried about the coding assignments but my TA (shoutout to alejandra arjon) spoonfed my section the code every week. the exams are pretty fair, not too hard or easy, and you get a doubled sided cheat sheet for each. there are two exams (week 5 and week 10) and a final coding project that you do with a group. it's pretty easy though and a group of 5-6 could knock that out easily. if you attend every lecture and do the clicker questions, you get 1% extra credit added to your final grade. professor cha was super sweet and accommodating!! this class was a super easy way to satisfy the life/physical science GE requirement

I took this class virtually over 6 weeks in Summer Session A. Grade distribution was 20% for homework, 20% for a final project, 25% for midterm or final (whichever grade was lower), and 35% for midterm or final (whichever grade was higher). Dr. Cha's syllabus, slides, and expectations for the course were extremely clear. I still tend to reference her slides for other courses and feel like I genuinely learned a lot. The grading of assignments was very fair. The only thing of note is that our two online exams required a lockdown browser with camera and audio on your device, but Dr. Cha was very proactive in making sure we knew she was available in case of any technical difficulties.

Amazing professor who I will be trying to take for every class she teaches. She is so clear and effective in her teaching. All of her homeworks align with the material and sufficient guidance is provided for them. There is a group project that allows you to showcase your new skills and meet other students. The exams are very fair and modeled well off of the lecture material and homework assignments. Overall I would recommend this class with this professor wholeheartedly.

Grading Scheme:
20% homework (5x4% each - 1 dropped)
20% group project
35% exam (the one with the higher grade)
25% other exam (the one with the lower grade)

Maria Cha is the best professor in the Stats department. Even better than Miles Chen. She is super nice, with very clear slides, case studies, and examples(!!!).

The grading scheme: 20% HW, 20% Group Project/Presentation, 25% midterm and 35% final OR 35% midterm and 25% final.

Homework: REALLY LONG. But doable. Discussions are optional and spent giving all the HW answers. Still do the hw though since the tests are similar. HW was mostly in R but also some by hand. Although you won't be tested on coding, you will need to know the contents/meaning of output tables in R like the back of your hand.

Group project: Simple data analysis and regression of a data set. Essentially use the code from HW on this project, make pretty slides, and slap together a 6 page report. Presentation was graded on completion, and pretty much all groups got a 100% on the final report.

Tests: Averages of ~90% for both. Most people finished the final in ~25 minutes. Very little math on either tests, but instead analyzing R output, taking information from an r output table and plugging it into an equation, and analyzing/explaining different graphs.

This class has incredibly useful content if you want to get into any sort of analytics/data science field. The p value is <0.05 which means the null hypothesis that this is a hard class, can be rejected, and we accept the alternate hypothesis that this class is an easy A.

Reading through the Bible in mandarin was easier to understand than her slides (I don't speak Mandarin).