STATS 101A
Introduction to Data Analysis and Regression
Description: Lecture, three hours; discussion, one hour. Requisites: one course from course 10, 12, 13, 15, Economics 41, or Psychology 100A, or score of 4 or higher on Advanced Placement Statistics Examination, and course 20. Recommended: course 102A. Applied regression analysis, with emphasis on general linear model (e.g., multiple regression) and generalized linear model (e.g., logistic regression). Special attention to modern extensions of regression, including regression diagnostics, graphical procedures, and bootstrapping for statistical influence. P/NP or letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Winter 2020 - I've literally never written a Bruinwalk review until this quarter after I had Almo for 101A. I've had the whole spread of stats professors from Chen, Tsiang, Christou, Zhou, and Sanchez and Almo is for sure the worst experience so far. To compare Almo and Sanchez, I felt that Sanchez was fairly organized. She had lecture notes, and a structured curriculum that go in a linear fashion. She may not be super nice but at least you know what you're learning about. Almo on the other hand is horrendously disorganized with regards to his notes, his lectures, his teaching, and his instructions. His lectures in particular feel that he is just YELLING words that are important but you have no idea what he's actually trying to teach. Not to mention, literally a whole question out of four questions on the midterm was unsolvable which was not mentioned until after the exam was graded meaning that we wasted a ton of time trying to solve this problem during the exam and likely lost points on the other parts of the exam. But overall, this class is not super hard. The homeworks aren't that hard and you can pretty much learn all the material in a day before the final by going through the textbook. But for sake of your sanity and feeling like you're getting your tuition's worth I would not recommend taking this class with Almo.
Winter 2020 - I've literally never written a Bruinwalk review until this quarter after I had Almo for 101A. I've had the whole spread of stats professors from Chen, Tsiang, Christou, Zhou, and Sanchez and Almo is for sure the worst experience so far. To compare Almo and Sanchez, I felt that Sanchez was fairly organized. She had lecture notes, and a structured curriculum that go in a linear fashion. She may not be super nice but at least you know what you're learning about. Almo on the other hand is horrendously disorganized with regards to his notes, his lectures, his teaching, and his instructions. His lectures in particular feel that he is just YELLING words that are important but you have no idea what he's actually trying to teach. Not to mention, literally a whole question out of four questions on the midterm was unsolvable which was not mentioned until after the exam was graded meaning that we wasted a ton of time trying to solve this problem during the exam and likely lost points on the other parts of the exam. But overall, this class is not super hard. The homeworks aren't that hard and you can pretty much learn all the material in a day before the final by going through the textbook. But for sake of your sanity and feeling like you're getting your tuition's worth I would not recommend taking this class with Almo.
Most Helpful Review
Winter 2024 - 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)
Winter 2024 - 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)
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Most Helpful Review
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.
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.
Most Helpful Review
Spring 2020 - This is by far one of my favorite Stats classes so far. Professor Gould is an incredible person and instructor. He was able to explain everything incredibly well and was tremendously active on Campuswire and answering emails. I personally enjoyed his use of participation in the class, it helped me from going insane to have some personal interaction with others during the Spring 2020, COVID-19 quarter. However, if you are anxious about these type of zoom breakout room activities, perhaps this class isn't for you because they happen almost weekly. (Prof gould would put us into breakouts and we'd explore the dataset he gave to us and do regression on it and stuff). The homeworks were pretty easy and didn't require a lot of R knowledge. It is a lot of repetition in terms of the looking at model adequacy and running lm() tests on data. There was not a final exam but rather a final project where you and a few other people (i was in a group of 2) investigate a dataset on your own and right a research paper (about 5 pages) on the topic. The project was easy and fun if you choose a fun topic that you're actually interested in. Grades were never a worry in the class, and was strongly right-skewed throughout the course. Even still, Prof gould curved the class on top of this distribution to ensure no one got lower than a C. I can't wait to take another course with him!
Spring 2020 - This is by far one of my favorite Stats classes so far. Professor Gould is an incredible person and instructor. He was able to explain everything incredibly well and was tremendously active on Campuswire and answering emails. I personally enjoyed his use of participation in the class, it helped me from going insane to have some personal interaction with others during the Spring 2020, COVID-19 quarter. However, if you are anxious about these type of zoom breakout room activities, perhaps this class isn't for you because they happen almost weekly. (Prof gould would put us into breakouts and we'd explore the dataset he gave to us and do regression on it and stuff). The homeworks were pretty easy and didn't require a lot of R knowledge. It is a lot of repetition in terms of the looking at model adequacy and running lm() tests on data. There was not a final exam but rather a final project where you and a few other people (i was in a group of 2) investigate a dataset on your own and right a research paper (about 5 pages) on the topic. The project was easy and fun if you choose a fun topic that you're actually interested in. Grades were never a worry in the class, and was strongly right-skewed throughout the course. Even still, Prof gould curved the class on top of this distribution to ensure no one got lower than a C. I can't wait to take another course with him!
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Most Helpful Review
Spring 2024 - Class Breakdown: 25% Five In-Class Quizzes (drops lowest quiz score) 20% Five Homework Assignments 20% Attending Class 20% Attending Class 20% Working with your TA during section Review: I have nothing bad to say about Professor Lew AT ALL. She cares so much about student health and wellbeing outside of class, she's literally like a close friend. She makes the class VERY REALISTIC to real life--the questions she asks are related to actual interview questions as if you were applying to become a Data Scientist. I haven't had a professor that is actually "real" in terms of going beyond just textbook and helping us develop us the skills necessary to survive in the real world. Attendance was mandatory BUT I have met so many new people that I have never met before in the same major as me which is honestly so sweet (and networking too haha). Slides were way easier to understand than the textbook. Also I'm pretty sure everyone got an A in this class because she grades leniently and gives out a lot of credit -- there's no "wrong" answer if you tried your best. I would 100000% take Professor Lew's class again in the future. TAKE HER!!! Thank you Professor Lew and I hope to see you again!
Spring 2024 - Class Breakdown: 25% Five In-Class Quizzes (drops lowest quiz score) 20% Five Homework Assignments 20% Attending Class 20% Attending Class 20% Working with your TA during section Review: I have nothing bad to say about Professor Lew AT ALL. She cares so much about student health and wellbeing outside of class, she's literally like a close friend. She makes the class VERY REALISTIC to real life--the questions she asks are related to actual interview questions as if you were applying to become a Data Scientist. I haven't had a professor that is actually "real" in terms of going beyond just textbook and helping us develop us the skills necessary to survive in the real world. Attendance was mandatory BUT I have met so many new people that I have never met before in the same major as me which is honestly so sweet (and networking too haha). Slides were way easier to understand than the textbook. Also I'm pretty sure everyone got an A in this class because she grades leniently and gives out a lot of credit -- there's no "wrong" answer if you tried your best. I would 100000% take Professor Lew's class again in the future. TAKE HER!!! Thank you Professor Lew and I hope to see you again!
Most Helpful Review
Winter 2021 - Took Stats 101A with Shi. 2021 Winter, remotely Good: few homework, less content each lecture, take-home exam(24hours) Bad: she is late more than 5 minutes EACH lecture, harsh grader, no reply email, no argument of Grade, the whole quarter content can be learned 5 weeks. I learn much more from TA. Quiz is tricky each week and easy to miss.
Winter 2021 - Took Stats 101A with Shi. 2021 Winter, remotely Good: few homework, less content each lecture, take-home exam(24hours) Bad: she is late more than 5 minutes EACH lecture, harsh grader, no reply email, no argument of Grade, the whole quarter content can be learned 5 weeks. I learn much more from TA. Quiz is tricky each week and easy to miss.
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