Summer 2021 - Not the best professor. She uploads pre-lecture videos and tells us we're "required" to watch them before lecture. Also she'll upload these videos at midnight.. or even a few hours before lecture, leaving us with little time to actually watch these before lecture time. However I didn't find any of these videos useful and her handwriting can be hard to read since she uses a pretty large pen size for her notes. Her actual lecture didn't seem that helpful to me. Her lecture is mostly her reading her notes and showing us coding in R, but it felt disorganized and all over the place. She also put us in breakout rooms to work on problem sets which she discusses the answers to after. I learned purely from the notes that she uploads to her CCLE site. The notes are okay, but they can look better. The notes have randomly chosen font sizes and there are some typos but if you understand the content, you can spot these. She uploads a bunch of files to CCLE but I recommend you use the notes and the "CFUs" to learn. The CFUs (Check for Understanding) are problem sets that deal with the topics we learn in lecture. She uploads the answers to them as well and these are great preparation for her midterms. We had 3 homework assignments but unfortunately we have to work on these assignments in a group. I wouldn't say these homework assignments are hard and long but it can be difficult working in a group when we're all in different time zones and when some people don't pull their weight. For the midterm and final, we were given a little bit more than 2 days to work on them. They're open notes, open book, open internet which was nice. They're about 4-5 questions with some questions having multiple parts, but the exams aren't too long and can be completed in 4-6 hours if you know what you're doing. They were pretty straightforward and mostly similar to the CFUs and homework. She also posts some previous midterm exams which definitely helped me study. The grading scheme is: Homework (20%), Midterm (40%), Final (40%) Homework assignments are graded very leniently and I think exam grading is fair. This class isn't difficult. Esfandiari isn't the best professor but she's nice and caring. She's disorganized at times but she cares about our learning. Despite all of this, I'm still happy with how much I learned from this class.
I really have no idea why the evaluations for her 101B course are so bad. The class wasn't bad at all and she's a very nice person in general. She's very willing to help students and cares a lot about everyone's progress. I guess some people might find the lectures useless, but for me, going to lecture was enough to get an A- with very little extra studying. Even when I missed 1 lecture, I found the notes to be pretty clear. The grading is actually fairly generous, so there's no need to sweat about your grade too much. It's not exactly a massive curve, but the class isn't nearly hard enough to warrant one. Overall, Mahtash is a pretty good teacher, and she has a motherly "aura" around her too (someone else mentioned something along these lines too). As for the class, Stats 101B isn't that hard, only slightly harder than 101A if anything. This can't even come close to the grueling 100ABC series. Would definitely recommend taking this class with her! If you do at least decent, you'll get a good grade.
Postives: -Really cares about student's understanding in the coursework. -Responds to emails promptly. -Helpful office hours. -Is a fair teacher. Negatives: -Handouts are very unreliable (filled with mistakes and errors all over the place). And what's worse, expects you to study off it. -Occasionally, if not often, makes mistakes on the board.
This professsor is one of the nicest I've had at UCLA. You can tell that she truly cares about her students. Her lectures are, however, pretty confusing. She does education-related research, and I think she tries to structure her lectures around her findings. Personally, I didn't find her way of teaching to be the most effective; I prefer a more traditionally structured course.
Fall 2018 - Grading breakdown: (15%) Four group homeworks & five labs (10%) Four reaction papers (2.5%) Evaluation by group member (individual grade) (2.5%) Lecture attendance when we have guest speaker (individual grade) (25%) Midterm (45%) Final exam The only pre-req for this course is STATS10, but if you take this class as a stats major, you will be assigned to Stats major homework group where you will be asked to do STATS101A~101C materials (up to interaction effects & random forests stuff for classification method). This class is so weired that different homework questions are assigned between non-stats and stats but all students take same midterm/final. When it comes to her teaching, she is not able to explain basic statistics concepts in a proper manner. I would be far behind and end up dropping this class if I were not a stats major. EVERY SINGLE her notes and slides has typos as well as her massive amount of emails. Students are actually taught by the TA, Narek. He teaches us pretty well though. Overall, I would not recommend this class at all. Whole quarter has been stressful to me because of two different reaction paper & homework assignment groups whose members reply my messages when homeworks are due + worst instructor who doesn't teach anything and keeps saying 'Do you understand me?'
Spring 2017 - Super easy class of course as essentially the last stats major course but worst lecturer I've had in my time at UCLA. Unfortunately, she's the only professor that teaches the course but in case you have another option in the future, I wouldn't take this with her! Her lecture slides and instructions are confusing so you never know what she expects or is asking of you. Her emails and lectures and handouts are filled with typos. Often times, she doesn't understand the question students are asking so its difficult to ask questions. Unorganized class, unorganized lecture, ineffective professor and difficult to communicate with. I'm sure she's nice and well known for her work academically, but definitely the worst professor which was a shame because this class was something the seniors looked forward to.
I am currently pursuing a graduate degree in a quantitative background and I can honestly say that Professor Esfandiari was one of the best professors I had during my years at UCLA. Much of what she has taught me (and this goes for the other professors in the stats. dept. as well) has helped me succeed this far in my graduate program. She really tries to teach you the fundamental ideas of what you are learning and why its important. Statistics isn't just a bunch of memorization that you cram the day before the test and regurgitate everything the day after only to forget it several days later. I think those who have a distaste for this professor fail to realize that. Additionally, it surprises me to see so many unnecessary slurs about the professors at UCLA about their accents, way of teaching, or the way they present themselves. I truly do not know how you go into this university--my hypothesis would be you probably had the very same foreign people write you your application essays or take your SAT's for you to get into the university. You are representing a university that is filled with diversity and culture- please remember that. Any who, you have evaluations at the end of the quarter to let them know how they did. Be mature and take the time to let them know what you thought of their teaching. They do take it seriously and appreciate the feedback. I'll end with this and say if you are willing to do the work and are actually interested in learning the subject of statistics, Esfandiari is right for you.