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54 Ratings
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— Students
With Gretchen Martinet, this class went pretty well. She's nice enough in lecture, but makes people talk in class. Not really a big deal though. You have the option of attendance being optional or not (if you need an incentive to go). I stopped going. Slides are posted online, I just looked at those. Following lecture, there's a 50 minute lab. Attendance was also optional and I never really went because most people didn't go either. You can just do the lab online, but you won't get help from the TA's (You could get away with going to other sections if you wanted also, but you must go to your sis one for exams). Labs aren't not hard and just based on the lecture with some experimentation with R. There's like 20 of them and you drop the 6 lowest. There's also a quiz each week, 5 questions, at home, pretty easy. 3 get dropped. These questions are more similar to what's on the exam. There's "homework" also, but its not graded and you don't submit anything, just practice problems. So outside of class, might only be about an hour or two of work.
Exams - there's 3, worth the same amount. Not cumulative. About 20 questions, 50 minutes in lab section. Little math on them, mostly conceptual. You get a cheat sheet, front and back. Can write like all of the slides down, you'll be solid. There's a textbook you could get more problems on, I never did this. Some questions are a bit tricky on the exams, just pay attention. It's not bad. I got an 82 on the first one, that's what got me an A- in the course.
Overall, with this teacher, everything is really forgiving. She's not bad at teaching either. Would recommend.
The course grade breakdown: weekly quizzes = 15%, weekly lab assignments = 25%, and three non-cumulative exams each = 20%.
Most people will agree that lecture is not helpful (she basically just reads off slides) so the optional attendance policy is very clutch. Obviously the downside is that you will primarily have to teach yourself. However, the assignments are a good reinforcement and will keep you on track with the material. As someone who was just taking this class to meet a requirement, I felt like the exams could be tricky. The assignments are not that similar to the exam questions and you are not given any practice exams to study. However, the weight of the labs and quizzes will SAVE you. The labs are group work with TAs there to help you, and the quizzes are straightforward. Not to mention, she drops three of your lowest quizzes and six of your lowest labs. Overall, the class is not an easy A, but it is VERY forgiving and you can do well.
Not to mention, Gretchen dropped the grade thresholds by 2% (with 1% from the course evals). She also MIGHT boost your grade if you demonstrated effort throughout the semester. So, maybe attending class more often than not would be worth it.
STAT 2120 with Martinet was a JOKE and if I can spare anyone the stress I would strongly suggest not taking this class with her if you have another option. If you don’t, buckle up, because it can be a rough experience. Lectures mainly consist of her reading directly off the slides with very little explanation which makes it difficult to actually understand the material. The course often feels more like an extended English class with only a small amount of statistics rather than a true stats course. Exams are noticeably harder than the material she covers in class, which is especially surprising given that you are allowed to use a front and back cheat sheet. There is a lab due every day there is class and each one is due at midnight. The lowest six lab grades are dropped at the end of the semester. There is also a weekly quiz and the lowest three quiz scores are dropped. Despite these drops, the workload and lack of clear instruction make the class unnecessarily stressful. Overall, I ended up teaching myself most of the material and honestly feel that my high school stats class was taught more clearly and effectively than this course.
I do wholeheartedly believe Professor Martinet needs to lock in how to devote herself to teaching, as this is the sheer responsibility she has to take care of as an associate professor who is not on a research track. This includes the lecture preparation, exam structure, and more relevant lab sessions. Especially considering the fact that this is an introductory course and a prerequisite for hundreds of students to take every semester, the quality and the overall experience of this course have been terrible—frankly speaking, completely unsatisfactory performance.
The fact that from the first class with full seats occupied by students to the final days where virtually the lecture room became like a small office-hour vibe tells everything: it is not worthy to even take a look at those slides where she will just read them line by line without any explanation or illustration of the concepts outside of PowerPoint, and then have pointless so-called “peer discussion” time (which is usually about 4 minutes long) for self-evident questions like “if Y = 2X, what is Y when X equals 1.”
I had large lectures and classes on math and statistics throughout my life; and as a person extremely interested in mathematics and statistics, this course miraculously made me feel sick about statistics and absolutely loathe it, as it is taught in an extremely tedious way. I really feel sad for students not able to enroll in this course because of the maximum student cap, because I know that even if 1,000 students are enrolled in this course taught by Gretchen, there would still be a plentiful amount of seats after one week. To be perfectly honest, ChatGPT is far more efficient, intelligent, and vivid than Gretchen, who is not willing to even talk about a single example outside of her black-and-white slides. By the way, this did not apply to any other course I have taken (even for courses like CS111X, where I thought ChatGPT could help a lot, but it turned out that lectures and the professors’ tutoring were far more intuitively understandable). I will not complain about the exam, though very intentionally tricky, I belive somebody else will talk about it.
Gretchen is also definitely a policy-wise volatile and unpredictable-without-limits one. The attendance policy was a joke; instead of making a uniform and standardized attendance policy for everyone, she added a thing called an optional attendance policy, where there is no consequence for not going to lectures and labs, whereas students enrolled in a mandatory attendance policy by default could be punished for their absences. This is one of the most hilarious things I have ever heard in my life. I do not know whether it is for research purposes or anything, but such differentiation and unfair negative feedback for those who actually attend class is inappropriate for a scheduled, large, introductory course in a college. Usually, an A is above 93, but pray for this since she will not tell you until the day she releases the grades.
Take Professor Holt's class if you need to take STAT 2120 is the last suggestion I can give to all students.
Don't take it with Martinet. All the labs require programming in R, but she never teaches it. At most she'll quickly spend 30 seconds (never more than 30 seconds) at the end of lecture going over what you need. If you go to lab, lab tas are super helpful and will usually just guide you to the right answers. You can also just gamble and not go to lab, or form a group and take turns going to lab. You get something like 5 drops for labs, so it's pretty lenient as well.
There were 3 midterms (noncumulative) that were in person and taken in your lab section. They were all tough, but fair. R isn't covered on the midterms (why even teach it? who knows.) so most of what you do in lab is useless anyways. The third midterm for Fall 2025 was cancelled because of snow, and she replaced it with the higher of your other midterm scores.
She's a pretty dry lecturer: she entirely reads off of the slides. If you have any small affinity for math you can skip every lecture and just read the slides. The last unit especially is terrible, since there are 5 slides introducing the new content and the remaining 35 slides are going through the same process of applying it to confidence intervals and tests (which are the same every week).
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