Professor
Michael Tsiang
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Most Helpful Review
Winter 2020 - Professor Michael Tsiang's lectures and slides are very helpful because he breaks everything down in order for it to be easy to understand. His exams are not easy A's however as you will find trick questions or oddly-worded questions causing you to get a B or B+ on his exams instead. But don't worry!!! I was below the mean on the first mid-term, but quite above the mean on the next mid-term and final. As long as you guys make sure you are at the mean for every exam, YOU WILL GET AN A! In addition, he gives very generous extra credit opportunities, which I made sure to capitalize on, make sure you do too. Although this class might make you stress out a bit, as long as you put in your effort, it is an easy A. I wish all his future students the best of luck. YOU GOT THIS!!!
Winter 2020 - Professor Michael Tsiang's lectures and slides are very helpful because he breaks everything down in order for it to be easy to understand. His exams are not easy A's however as you will find trick questions or oddly-worded questions causing you to get a B or B+ on his exams instead. But don't worry!!! I was below the mean on the first mid-term, but quite above the mean on the next mid-term and final. As long as you guys make sure you are at the mean for every exam, YOU WILL GET AN A! In addition, he gives very generous extra credit opportunities, which I made sure to capitalize on, make sure you do too. Although this class might make you stress out a bit, as long as you put in your effort, it is an easy A. I wish all his future students the best of luck. YOU GOT THIS!!!
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Most Helpful Review
Winter 2024 - I decided for my reviews now I will now justify my scores for each of the components as well as a more extensive review: Number Score Overview: Easiness: 5 - Class content is not that difficult, exams are fair (NOTE: Took AP Stats in Highschool) Clarity: 5 - He is very clear and great at explaining the statistical concepts Workload: 5- The workload is not that bad, homework assignments can sometimes be long but not too bad, but it wasn't something completely unmanageable. Helpfulness: 5- Mike was super helpful his office hour as well as the TAs. There was alot of support in that class to get the help you need. Overall: 4- Overall this class was fine, I was a little bored but that's probably because I had learned the content before and it was very slow paced. I hated the labs, I did not learn anything and probably will forget the few things I remember about r. Content is interesting but go over less stuff compared to AP Stats. Extensive Review: Professor: Mike is a decent professor. He is really nice and really cares about your mental and emotional wellbeing. He is great at explaining things and he can be pretty funny if that's your sense of humor. Class: The class is fine, a normal introductory statistics class. If you took AP Stats in highschool its pretty much the same thing except with less content. The main difference is that AP Stats covered more topics and focused more on theoretical stuff while this class focuses on what happens if theoretical conditions are not met and how to conduct these tests using simulation. The labs were pretty boring, did not learn much. I was just copying down whatever the TA. There will be coding on your exams so you should try harder on it than I did. The homework can be a bit long but for whatever reason, whoever is grading the homework is such a stickler for the smallest things. I would get the stupidest points marked off on my homework for the most random things. So just be aware of that.
Winter 2024 - I decided for my reviews now I will now justify my scores for each of the components as well as a more extensive review: Number Score Overview: Easiness: 5 - Class content is not that difficult, exams are fair (NOTE: Took AP Stats in Highschool) Clarity: 5 - He is very clear and great at explaining the statistical concepts Workload: 5- The workload is not that bad, homework assignments can sometimes be long but not too bad, but it wasn't something completely unmanageable. Helpfulness: 5- Mike was super helpful his office hour as well as the TAs. There was alot of support in that class to get the help you need. Overall: 4- Overall this class was fine, I was a little bored but that's probably because I had learned the content before and it was very slow paced. I hated the labs, I did not learn anything and probably will forget the few things I remember about r. Content is interesting but go over less stuff compared to AP Stats. Extensive Review: Professor: Mike is a decent professor. He is really nice and really cares about your mental and emotional wellbeing. He is great at explaining things and he can be pretty funny if that's your sense of humor. Class: The class is fine, a normal introductory statistics class. If you took AP Stats in highschool its pretty much the same thing except with less content. The main difference is that AP Stats covered more topics and focused more on theoretical stuff while this class focuses on what happens if theoretical conditions are not met and how to conduct these tests using simulation. The labs were pretty boring, did not learn much. I was just copying down whatever the TA. There will be coding on your exams so you should try harder on it than I did. The homework can be a bit long but for whatever reason, whoever is grading the homework is such a stickler for the smallest things. I would get the stupidest points marked off on my homework for the most random things. So just be aware of that.
Most Helpful Review
Fall 2020 - It has been a whole year since the last review, and there have been some changes since then. I hope this long review/guide will give you a better understanding of what this class will be like: ***1. Grading Structure (original scheme on the syllabus, see comment for adjustments and actual grading structure): 18% Homework, 20% MT 1, 20% MT 2, 30% Final, 12% Final Project, 1% Extra credit for Discussion Attendance, 0.5% Extra credit for Campuswire participation - Mike made several adjustments during the quarter to alleviate stress for students, including: #1. Canceling the final project #2. Allocating 25 pts to the better MT score and 15 to the other. #3. Grading the homework on satisfactory completion, rather than correctness (although the graders will provide helpful comments if your code doesn’t pass certain cases). #4. Dropping the lowest homework (best 7 out of 8) and #5. Giving everyone the attendance credit ***2.Grade distributions: MT1: Mean 62.67; Quartiles: 55, 61.67, 76.25 MT2: Mean 64.47; Quartiles: 51.67, 65, 76.67 Final: Mean 67.9; Quartiles: 55.56, 68.89, 80 Don’t get scared yet and read on. According to the professor, here is your rough letter grade break down (before the curve at the end of the quarter) if your performance is consistently: In the lower 25% (x < Q1): B/B- In the lower 25%-50% (Q1 < x < Q2): A-/B+/B In the upper 25%-50% (Q2 < x < Q3): A/A- In the upper 25% (x > Q3): A+/A ***3.General remarks: --> On lectures: Professor Tsiang uploads lecture videos ahead of time, so the scheduled lecture times are really office hours. I recommend watching the lectures ahead of time and coming to OH with questions about concepts or HW. Although Mike follows his lecture notes closely in the videos, you should still watch the lectures instead of just reading the notes, since you see the process of building functions (plus the professor will mention some small examples and conceptual details that are not in the notes) --> On homework: the homework assignments are graded on satisfactory completion so don’t panic if you are stuck on a question. Try to complete as many parts as you can and write out pseudocode/ thoughts on how the logic should go for the others that you are stuck on. There is also a 1 day grace period (meaning you can submit your homework up to 24 hours late without penalty). I don’t recommend stressing and working on the HW till the last minute of the grace period. It’s better to turn in parts that show effort than pushing for the complete solution and missing the deadline. The professor and the learning assistant are willing to discuss the homework with you after submission so you can always go back and finish the solution. --> On getting help: You should definitely ask questions on Campuswire, which is pretty active (Mike responds quickly, and other students give advices as well). There are a few things to note: #1. Please search up if someone has already asked the question and has gotten an answer. Professor Tsiang and the TAs in this case will most likely just respond with a link to the old post. #2. Both Mike and the TAs do not like giving away too much of the answer and their hints may seem “cryptic”. Please be patient and know that this is the necessary struggle for you to figure something out slowly on your own. Feel free to follow up after you have made a little progress with that hint to get the next hint. My suggestion for you is to discuss your thought process with Mike at his OH, where he is more prone to give away a bit too much ;) --> On this course’s reputation: Stats 20 seems to have a notorious reputation now mainly due to students’ past experiences with Jake. Here’s my thought and I implore you to read it through before judging. Jake is very knowledgeable in the course material and passionate about student learning. He is, however, not the most patient when students ask questions that have been answered before or do something in the code that is explicitly forbidden in the instructions. If you paid attention to the lectures, followed the rules, and asked a thoughtful question, he will most definitely try to give you a helpful response (subject to #2 from “On getting help”). Jake wants to challenge students to think about how could everything go wrong, which is why he focuses on edge cases; this is why I think him being a not-so-beginner-friendly TA for a very tough class really stresses out students and makes them feel like he is adding unnecessary difficulty. If you disagree with my thoughts, that is fine. I also agree that Jake can try to be more approachable to reduce unintentional tension in interactions with students. HOWEVER, I ask you to please voice your suggestions/frustrations in your course evaluations, not on Reddit. We have had enough posts that it has descended into a trend of hate bashing (I suspect that there are individuals who have not even take the course writing on the posts). I write my review here also so that it does not get drowned out immediately by mindless downvotes. I do not want this to become a hateful “urban legend” that scares off students who are interested in Stats and want to take this class. Anonymity allows lots of toxicity in the threads, and I urge you not to add more. For everyone who took Stats20 this fall, if you think I am BSing or doubt my identity, feel free to reach out and talk to me - R.B. --> On difficulty and succeeding in this class: The class is very challenging but will cover many key concepts that will allow you to straight-up start working on some data analysis projects. You will need to devote lots of time to homework and should do some exploring on your own (playing with functions and see how they work together) to truly get a strong understanding. Mike will tell you many times to focus on the learning and let him take care of the grades. Please have some faith in his statement, even if you are struggling, because he does mean it. As you can see from the stats from the Grade distribution section, your numeric score doesn’t even come close to the letter grade you may associate it with. Mike spends a lot of time at the end of the quarter applying curves and assigning grades because he knows it is a hard class. Have faith in yourself. You most definitely will not come even close to failing if you’ve put in the effort. Lastly, if you need help - an HW extension or reschedule MT due to time zone - reach out to Mike; he cares about students’ mental being and is aware of the difficult times we live in. I am sure he will help you out as much as he can.
Fall 2020 - It has been a whole year since the last review, and there have been some changes since then. I hope this long review/guide will give you a better understanding of what this class will be like: ***1. Grading Structure (original scheme on the syllabus, see comment for adjustments and actual grading structure): 18% Homework, 20% MT 1, 20% MT 2, 30% Final, 12% Final Project, 1% Extra credit for Discussion Attendance, 0.5% Extra credit for Campuswire participation - Mike made several adjustments during the quarter to alleviate stress for students, including: #1. Canceling the final project #2. Allocating 25 pts to the better MT score and 15 to the other. #3. Grading the homework on satisfactory completion, rather than correctness (although the graders will provide helpful comments if your code doesn’t pass certain cases). #4. Dropping the lowest homework (best 7 out of 8) and #5. Giving everyone the attendance credit ***2.Grade distributions: MT1: Mean 62.67; Quartiles: 55, 61.67, 76.25 MT2: Mean 64.47; Quartiles: 51.67, 65, 76.67 Final: Mean 67.9; Quartiles: 55.56, 68.89, 80 Don’t get scared yet and read on. According to the professor, here is your rough letter grade break down (before the curve at the end of the quarter) if your performance is consistently: In the lower 25% (x < Q1): B/B- In the lower 25%-50% (Q1 < x < Q2): A-/B+/B In the upper 25%-50% (Q2 < x < Q3): A/A- In the upper 25% (x > Q3): A+/A ***3.General remarks: --> On lectures: Professor Tsiang uploads lecture videos ahead of time, so the scheduled lecture times are really office hours. I recommend watching the lectures ahead of time and coming to OH with questions about concepts or HW. Although Mike follows his lecture notes closely in the videos, you should still watch the lectures instead of just reading the notes, since you see the process of building functions (plus the professor will mention some small examples and conceptual details that are not in the notes) --> On homework: the homework assignments are graded on satisfactory completion so don’t panic if you are stuck on a question. Try to complete as many parts as you can and write out pseudocode/ thoughts on how the logic should go for the others that you are stuck on. There is also a 1 day grace period (meaning you can submit your homework up to 24 hours late without penalty). I don’t recommend stressing and working on the HW till the last minute of the grace period. It’s better to turn in parts that show effort than pushing for the complete solution and missing the deadline. The professor and the learning assistant are willing to discuss the homework with you after submission so you can always go back and finish the solution. --> On getting help: You should definitely ask questions on Campuswire, which is pretty active (Mike responds quickly, and other students give advices as well). There are a few things to note: #1. Please search up if someone has already asked the question and has gotten an answer. Professor Tsiang and the TAs in this case will most likely just respond with a link to the old post. #2. Both Mike and the TAs do not like giving away too much of the answer and their hints may seem “cryptic”. Please be patient and know that this is the necessary struggle for you to figure something out slowly on your own. Feel free to follow up after you have made a little progress with that hint to get the next hint. My suggestion for you is to discuss your thought process with Mike at his OH, where he is more prone to give away a bit too much ;) --> On this course’s reputation: Stats 20 seems to have a notorious reputation now mainly due to students’ past experiences with Jake. Here’s my thought and I implore you to read it through before judging. Jake is very knowledgeable in the course material and passionate about student learning. He is, however, not the most patient when students ask questions that have been answered before or do something in the code that is explicitly forbidden in the instructions. If you paid attention to the lectures, followed the rules, and asked a thoughtful question, he will most definitely try to give you a helpful response (subject to #2 from “On getting help”). Jake wants to challenge students to think about how could everything go wrong, which is why he focuses on edge cases; this is why I think him being a not-so-beginner-friendly TA for a very tough class really stresses out students and makes them feel like he is adding unnecessary difficulty. If you disagree with my thoughts, that is fine. I also agree that Jake can try to be more approachable to reduce unintentional tension in interactions with students. HOWEVER, I ask you to please voice your suggestions/frustrations in your course evaluations, not on Reddit. We have had enough posts that it has descended into a trend of hate bashing (I suspect that there are individuals who have not even take the course writing on the posts). I write my review here also so that it does not get drowned out immediately by mindless downvotes. I do not want this to become a hateful “urban legend” that scares off students who are interested in Stats and want to take this class. Anonymity allows lots of toxicity in the threads, and I urge you not to add more. For everyone who took Stats20 this fall, if you think I am BSing or doubt my identity, feel free to reach out and talk to me - R.B. --> On difficulty and succeeding in this class: The class is very challenging but will cover many key concepts that will allow you to straight-up start working on some data analysis projects. You will need to devote lots of time to homework and should do some exploring on your own (playing with functions and see how they work together) to truly get a strong understanding. Mike will tell you many times to focus on the learning and let him take care of the grades. Please have some faith in his statement, even if you are struggling, because he does mean it. As you can see from the stats from the Grade distribution section, your numeric score doesn’t even come close to the letter grade you may associate it with. Mike spends a lot of time at the end of the quarter applying curves and assigning grades because he knows it is a hard class. Have faith in yourself. You most definitely will not come even close to failing if you’ve put in the effort. Lastly, if you need help - an HW extension or reschedule MT due to time zone - reach out to Mike; he cares about students’ mental being and is aware of the difficult times we live in. I am sure he will help you out as much as he can.
Most Helpful Review
Spring 2020 - It was Mike's first time teaching 100C, yet he always made organized, informative slides for each lecture and reasonable but challenging homework assignments. He also was very accommodating at the end because of everything surrounding the protests and riots. 100C gets a rep for being one of the hardest stats classes, but I felt Mike's instruction and expectations made it a very fulfilling, enjoyable experience. Really pleased to have taken it with him!
Spring 2020 - It was Mike's first time teaching 100C, yet he always made organized, informative slides for each lecture and reasonable but challenging homework assignments. He also was very accommodating at the end because of everything surrounding the protests and riots. 100C gets a rep for being one of the hardest stats classes, but I felt Mike's instruction and expectations made it a very fulfilling, enjoyable experience. Really pleased to have taken it with him!
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Summer 2019 - I took mike's stats 20 before, mike is very nice, especially on curving. I was glad that I took his 102A, but unfortunately we had a WORSE TA. In my session, 50% hw, 10% midterm, 10% midterm project, 15% final exam, 15% final project, 0.5% campus wire for extra credit. I do not know why and how can one TA do so much stuff. If you have JAKE as TA, drop the class. JAKE is the WORSE TA I have ever met in UCLA. felt like JAKE made all the hw, and hw never matched the lecture, they were not on the same level, it just like prof. teach you how to calculate 1+1, and the hw ask you to take the partial derivative of the function. Midterm project, final project tough. The midterm was super TOUGH, within 50 mins, undoable questions. Final was better than midterm but still TIOUGH and not related to the lecture. I felt sad that I did not hear JAKE before 102A, if I know he is this kind of person, I would drop the class immediately. TRUST ME.
Summer 2019 - I took mike's stats 20 before, mike is very nice, especially on curving. I was glad that I took his 102A, but unfortunately we had a WORSE TA. In my session, 50% hw, 10% midterm, 10% midterm project, 15% final exam, 15% final project, 0.5% campus wire for extra credit. I do not know why and how can one TA do so much stuff. If you have JAKE as TA, drop the class. JAKE is the WORSE TA I have ever met in UCLA. felt like JAKE made all the hw, and hw never matched the lecture, they were not on the same level, it just like prof. teach you how to calculate 1+1, and the hw ask you to take the partial derivative of the function. Midterm project, final project tough. The midterm was super TOUGH, within 50 mins, undoable questions. Final was better than midterm but still TIOUGH and not related to the lecture. I felt sad that I did not hear JAKE before 102A, if I know he is this kind of person, I would drop the class immediately. TRUST ME.
Most Helpful Review
Spring 2024 - Great class. It was his first time teaching 102B, but he was able to teach all of the topics and explain them really well. The material is almost identical to Math 156 and its a cool and relevant class for understanding machine learning. Lectures are recorded and aren't mandatory. HWs really help you understand the concepts and they're easy enough to do in one sitting. Exams are also not so bad, and he emphasizes the importance of mental health and not worrying too much about your grade with lots of motivational speeches. Michael and Miles are my top 2 for stats profs, so I was pleased to take his class.
Spring 2024 - Great class. It was his first time teaching 102B, but he was able to teach all of the topics and explain them really well. The material is almost identical to Math 156 and its a cool and relevant class for understanding machine learning. Lectures are recorded and aren't mandatory. HWs really help you understand the concepts and they're easy enough to do in one sitting. Exams are also not so bad, and he emphasizes the importance of mental health and not worrying too much about your grade with lots of motivational speeches. Michael and Miles are my top 2 for stats profs, so I was pleased to take his class.
Most Helpful Review
Summer 2020 - I love Mike omg he's one of my favorite professors in the stats dept. He really cares about his students and wants us to deeply understand the material that he's so passionate about (he literally said every method we learned in this class was his favorite lol). I also had him for Stats 20 in Fall 2019 (which is when the homework/tests changed although it was still a great class, most people just complained cause of grading and making you think critically in a different way imo). Mike's 102C is more on the theoretical side than Prof Miles Chen, but there is still programming in R for simulations and sampling. Def brush up on 100B as you'll need it. Mike is helpful in OH and on Campuswire, and we got 1% EC for Campuswire or attending discussions (grading scheme 40% HW 60% final). He gave us 48 hours on our take home final (no internet, only class notes) which was incredibly generous. His homework and exams are just extensions of his lecture slides. Lectures were prerecorded and during our "lecture time" it was basically OH. Would recommend taking a class with Mike if you can!
Summer 2020 - I love Mike omg he's one of my favorite professors in the stats dept. He really cares about his students and wants us to deeply understand the material that he's so passionate about (he literally said every method we learned in this class was his favorite lol). I also had him for Stats 20 in Fall 2019 (which is when the homework/tests changed although it was still a great class, most people just complained cause of grading and making you think critically in a different way imo). Mike's 102C is more on the theoretical side than Prof Miles Chen, but there is still programming in R for simulations and sampling. Def brush up on 100B as you'll need it. Mike is helpful in OH and on Campuswire, and we got 1% EC for Campuswire or attending discussions (grading scheme 40% HW 60% final). He gave us 48 hours on our take home final (no internet, only class notes) which was incredibly generous. His homework and exams are just extensions of his lecture slides. Lectures were prerecorded and during our "lecture time" it was basically OH. Would recommend taking a class with Mike if you can!
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