STATS 20
Introduction to Statistical Programming with R
Description: Lecture, three hours; discussion, one hour. Enforced requisite: course 10, 12, or 13. Designed to prepare students for upper-division work in statistics. Introduction to use of R, including data management, simple programming, and statistical graphics in R. P/NP or letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Summer 2020 - Professor Lew is absolutely fantastic. Having come in with little to no programming experience (AP CS in high school), she makes learning R fun. Especially during COVID, she has been so understanding of students' struggles (e.g. recording lectures, providing opportunities for up to 10% extra credit, dropping lowest grades). Though she might seem intimidating, I would recommend anyone to attend her office hours at least once: she has so much professional experience in the stats field (i.e. not just as a professor) as well as so much wisdom to offer. This class is primarily based on projects and assignments, and unlike the other professor who teaches Stats 20, there are no formal exams. I'd say that it is very easy to earn a decent grade if you put your best foot forward; even if she were not as lenient because of the pandemic, I'd assume it'd be the same. Although I haven't received my final grade yet, I'm very confident about my performance in her class because she makes it clear how to earn points/what she's looking for (tip: don't over analyze instructions!). Some other notes: (1) there is no curve for the course, though I don't see when one would be needed and (2) don't get the recommended textbook. Because of her, I feel like I have a solid understanding of R and have decided to pursue a minor in stats! I'd love to take any future courses with her.
Summer 2020 - Professor Lew is absolutely fantastic. Having come in with little to no programming experience (AP CS in high school), she makes learning R fun. Especially during COVID, she has been so understanding of students' struggles (e.g. recording lectures, providing opportunities for up to 10% extra credit, dropping lowest grades). Though she might seem intimidating, I would recommend anyone to attend her office hours at least once: she has so much professional experience in the stats field (i.e. not just as a professor) as well as so much wisdom to offer. This class is primarily based on projects and assignments, and unlike the other professor who teaches Stats 20, there are no formal exams. I'd say that it is very easy to earn a decent grade if you put your best foot forward; even if she were not as lenient because of the pandemic, I'd assume it'd be the same. Although I haven't received my final grade yet, I'm very confident about my performance in her class because she makes it clear how to earn points/what she's looking for (tip: don't over analyze instructions!). Some other notes: (1) there is no curve for the course, though I don't see when one would be needed and (2) don't get the recommended textbook. Because of her, I feel like I have a solid understanding of R and have decided to pursue a minor in stats! I'd love to take any future courses with her.
Most Helpful Review
Fall 2017 - Horrible horrible class. I had crippling anxiety and walking into this class tipped me over the edge. Her homeworks are overload and are carelessly created (full of mistakes and unclear directions) -- however because of this she is lenient on the grading. The group "quizzes" she assigned took an entire weekends worth of time and she ended up handing out A's to everyone that completed it. Contradicts herself a lot during lecture and has an attitude. For example in the beg of the quarter she would get mad at people who would just listen to her instead of taking notes, and she said "What are you guys doing? You guys should be typing and not just listening... you need to turn this in. Please get busy". Later on during the quarter when we are typing what she's typing, she yells "Can you guys please stop typing. Just listen.". Always lets us out late -- this is a problem because she opens up submission forms for in class participation activities when class is supposed to be dismissed and she talks about the weekends homework assignment after the class is supposed to end.... always end up being 5 minutes late to my next class. Last thing: Grading is very inconsistent. First 3 or so quizzes were grader rather rigorously. Average was a C, but towards the end the quiz averages were 90-95. Not sure whether this class was curved or raw scored, but if it was curved, this method makes it impossible to beat the class average and better your grade especially if you got off to a poor start. Tips for prof: End class on time and make more manageable homeworks. Also keep grading consistent please.
Fall 2017 - Horrible horrible class. I had crippling anxiety and walking into this class tipped me over the edge. Her homeworks are overload and are carelessly created (full of mistakes and unclear directions) -- however because of this she is lenient on the grading. The group "quizzes" she assigned took an entire weekends worth of time and she ended up handing out A's to everyone that completed it. Contradicts herself a lot during lecture and has an attitude. For example in the beg of the quarter she would get mad at people who would just listen to her instead of taking notes, and she said "What are you guys doing? You guys should be typing and not just listening... you need to turn this in. Please get busy". Later on during the quarter when we are typing what she's typing, she yells "Can you guys please stop typing. Just listen.". Always lets us out late -- this is a problem because she opens up submission forms for in class participation activities when class is supposed to be dismissed and she talks about the weekends homework assignment after the class is supposed to end.... always end up being 5 minutes late to my next class. Last thing: Grading is very inconsistent. First 3 or so quizzes were grader rather rigorously. Average was a C, but towards the end the quiz averages were 90-95. Not sure whether this class was curved or raw scored, but if it was curved, this method makes it impossible to beat the class average and better your grade especially if you got off to a poor start. Tips for prof: End class on time and make more manageable homeworks. Also keep grading consistent please.
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.