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: Please check the eligibility rules. No prior knowledge of Statistics is required. NOTE: SDS 3030 (Math/SDS 3211) and SDS 3020 (Math/SDS 3200) can not both count towards any major or minor in the Statistics and Data Science Department.
Instructors
Reviews
Super nice professor, very focused on students and helping us learn. Exams were similar to homeworks, and we had extra credit on some
5/28/2026
SDS 3030 is a class with hard content, the class moves very fast but Prof. Moncada is very good at explaining each concept. If you go to lectures you should be fine.
4/28/2026
I took Statistics for Data Science I with her. She is a good professor and cares for her students a lot. However, she makes mistakes on her slides almost every lecture, and her explanations are not the best for statistical concepts. Her exams are pretty long for an in-class exam as most of us did not have time to double check the exams.
1/18/2026
This class is a moderately difficult class, but interesting and useful. The final project was really interesting. I like Jager a lot and she is really nice, but I don't love the way she formats her notes (even though it works great for most people). You should definitely take this class and Jager is great!
12/17/2025
(Stats 3030) Moncada is super sweet and very accessible. Although, I didn't feel like I always had enough time on exams they did reflect what we did in class. However, a lot of it was computations that you need to know from calc 3. It is not an easy class, but it's interesting. If you stay on top of the work and go to office hours you will be fine.
12/12/2025
Kind and energetic. Content is pretty interesting. Exam problems are very computational and easier than HWs but harder computations than that of the calc classes.
12/7/2025
Lectures are very average. She posts all her notes so no need to go to lecture. She is very helpful in OH for hw and other questions. Though, her exams are a bit tough. Knowing the concepts helped, but I lost too many points making small mistakes. Class content is anything too crazy. If you took AP stats you'll be extra chilling.
5/21/2025
She is a great professor, but be aware of this class is not same with 3200--the content is more probability-based and exams are a little more difficult. Her exams are sometimes difficult, and the average is not high if she does not give you extra credit. Please prepare well for the final. Exams worth 75% of the total score.
5/5/2025
Prof Moncada-Morales is a sweet person, but content is challenging, and she can put unexpected curveballs on exams. Super accessible outside of class though, so take I wouldn't say take with caution, but know you're in for a lot of work.
4/30/2025
Do not take this class unless you absolutely have to for a data science major. Moncada is a very nice lady but she just reads off equations and formulas in class and her exams (which are 50-minute, in class that each make up 25% of your grade) are brutal. I lost my 4.0 in ugly fashion with this class.
4/29/2025
SUCH an amazing professor!! She genuinely cares about students, is super approachable, and accessible outside of class. The content can be tough, but totally manageable if you go to lecture. Also, if you study, the exams are very fair and reflect what she teaches. If you put in the effort, you'll have a great experience. Highly recommend!!
4/11/2025
Do not take class with Professor Morales. Her tests are ridiculous, and she is very unhelpful. She consistently has errors in the homework solutions and even left off part of a test question and only realized in the last 10 minutes of the test. She didn't even give us points back on the question. Very harsh.
4/10/2025
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