Introduction to data science. Concepts of statistical thinking. Topics include random variables, sampling distributions, hypothesis testing, correlation and regression. Visualizing, analyzing and interpreting real world data using Python. Computing labs required.
5
UnitsOptional
Grading1, 2
PasstimeNone
Level LimitLetters and science
CollegeThere was 1 prerecorded lecture and 1 in person lecture per week. The prerecorded lecture was laid out very well so it was easy to take notes and follow along, in person lecture was a review of the recorded one. She curved the final grade. I highly recommend because I'm already recognizing irl concepts that I learned from this class.
Professor Swenson is genuinely one of the kindest people ever. Math isn't my forte and I was really intimidated coming in but she broke down concepts so well and provided so many examples for everything which really helped me. Love her!!! (also the python aspect of this class isn't super serious so don't worry)
Professor Swenson is really nice. Really passionate about the contents, and would answer a lot of questions you have through easier examples. Though the lectures do need to take some time to adapt to and finish them, but you can do the lectures with your own pace (since part of them are online). A caring professor that can lead you into statistics.
Professor Swenson is a sweetheart, caring for her students success. Half the class is asynchronous, so it's nice to go at my own pace and then review the lectures once in person. The only difficulty was 80% was graded on exams, and 20% on participation/attendance. No HW credit, but you are expected to do HW to maintain a good grade.