STAT 1601

As someone who had never touched coding, Prof. Roland made this class super approachable! I was not excited to take this class as a psych major with no interest in coding, but that completely changed. Prof. Roland is very friendly and willing to answer all the questions we had with coding. Grades were composed of weekly homework (30%), weekly quizzes (20%), three class activities (10%), final project check ins (10%), and the final project (30%). The first half of the semester, the homeworks took me 30 mins max, but as we got deeper into coding, the later ones took me 2+ hours, but they were all very doable. There are also 8 TA office hours per week and a Piazza board that Prof. Roland is responsive on. For quizzes, they were timed for around 20 minutes, and we had two attempts and our score was averaged. She also let us drop our lowest homework/quiz grade which was helpful. It is easy to succeed in this class with the vast number of assignments and the availability of support. The only thing I would note is that Prof. Roland is not flexible with turning things in late. If you forget to turn something in, too bad. She seems really strict with this policy, but also has the built in drop homework/quiz to balance that out, so it's your responsibility to stay on top of the work. Overall, I highly recommend this class with Prof Roland! She is very friendly, knowledgeable, and committed to us succeeding, just make sure you turn things in on time and utilize the resources available. #tCFS24

(Semester was Fall 2023 but there was no option)
Really fair professor; every assignment was announced far in advance with email reminders leading up to each; quizzed content was never rushed, always drew from at least 2 lectures back; prof was considerate of holidays/busy periods and would avoid scheduling deadlines then. Nice organization where all class notes were basically transcribed in the day's R file, and solutions to class problems were posted afterward. Canvas page was also very organized and easy to refer back to. Overall, just a really organized class with a fair, transparent, organized professor that makes the whole experience smooth! Grade breakdown was 40% HW, 20% Check-ins (short canvas quizzes once in a while), 40% final project. Course content was a very practical starting pt for data sci I think! Learned how to write in base R and use popular libraries like dplyr, tidyr, and ggplot. Some skills u learn are basic data cleaning, data wrangling, finding summary statistics, data visualizations like scatter plots and histograms. Course doesn't go too deep into Statistics but the towards the end u have a unit on hypothesis testing, so you will learn how to use R to find test null hypotheses, find its p-value, etc.