SDS 3030
Statistics for Data Science I
This course starts with an introduction to R that will be used to study and explore various features of data sets and summarize important features using R graphical tools. It also aims to provide theoretical tools to understand randomness through elementary probability and probability laws governing random variables and their interactions. It integrates analytical and computational tools to investigate statistical distributional properties of complex functions of data. The course lays the foundation for statistical inference and covers important estimation techniques and their properties. It also provides an introduction to more complex statistical inference concepts involving testing of hypotheses and interval estimation. Required for students pursuing a major in Data Science. Prerequisite: Multivariable Calculus (Math 233). No prior knowledge of Statistics is required. NOTE: Math/SDS 3211 and Math/SDS 3200 can not both count towards any major or minor in the Statistics and Data Science Department.
Instructors
Reviews
Icon. Learned more from her two classes than from the rest of the math department put together - wish the school had more professors like her!
5/10/2024
You can clearly tell she really knows her material and loves teaching. My biggest criticisms are sometimes it feels like we would learn a very theoretical concept and then go straight into challenging applications of that theory. Also, I wish we had more practice problems or some sort of a study guide for the exams.
11/20/2023
Tests are 70% of the grade but are much easier than in class problems, and similar or easier than HW problems. Content slowly goes from a 2/10 to 8/10 in difficulty, but she is always eager to explain things and help. Weekly problem sets that take 1-7 hours. 60 minutes of required videos per week. I would take this class again if she is teaching
11/17/2023
Professor Jager teaches a great class. 3211 is a lot of material by nature and it can get overwhelming. She was very helpful and accessible after class, during office hours, etc for any questions. Exams were allowed a cheat sheet of formulas. Definitely would take it again, one of the coolest stats professors in the department!
1/22/2023