Which Statistics Course?

If you are not a Statistics major, but you would like (or you need) to take Statistics, please note that the Statistics Department offers several classes geared towards non majors who would like to understand statistics at different levels, either at a more conceptual and introductory level, or in its computational aspects or as a tool to gain visualize and communicate data and results. 

Introductory classes

The Statistics Department offers several introductory courses which provide Natural World (NW) and Quantitative and Symbolic Reasoning (QSR) general education credits. Each course is geared towards a slightly different audience. For a full description of these courses, content and prerequisites, please visit our course catalog.   

STAT 220, STAT/CSSS/SOC 221, and STAT 311 are by far our most popular (and widely applicable) introductory courses. As illustrated in the flowchart below, STAT 311 is geared to students aiming for more quantitative disciplines: STAT, BUSINESS, ECON, and INFO among others. (It is, however, NOT intended for students in E.N.G.R., MATH, A.C.M.S. as these disciplines require STAT 390.  Students should check requirements with their major advisors.)  On the other hand, STAT 220 and STAT 221 focus on statistical literacy and logical thinking and are geared towards the non-mathematical student. The aim is to develop quantitative problem-solving skills as well as build a statistical vocabulary. If your interests are in the social sciences, and you would otherwise take STAT 220, consider STAT 221 instead. 

Image of chart for non-major courses

STAT/CSE 180 is a relatively recent alternative which introduces the essential elements of data science. It is a good choice for students looking for a hybrid between a computer course and a statistics course. It is not intended for students who have taken statistics courses such as STAT 220, 221, 311 or 390 or programming courses like CSE 160.

Machine Learning classes 

The Department of Statistics offers various classes with the goal of introducing students to theory and applications of machine learning methodologies, technologies, and algorithms. The most popular options are STAT/CSE 416 and STAT 435. Students entering these classes should have some knowledge of probability, statistics, and algorithms, as reflected by these courses’ pre-requites (see the course catalog for more details on the pre-requisites). STAT/CSE 416 is a machine learning course designed for non-STAT and non-CSE majors and it requires some prior coursework in probability and statistics as well as a course in computer science. STAT/CSE 416 relies on programming in Python, while STAT 435 relies on programming in R. STAT 435 is geared towards Statistics majors and students with a stronger mathematical background. It covers similar topics to STAT/CSE 416, but it provides a deeper theoretical understanding of the methods.  

STAT 416 is a popular choice among non-Statistics students who major in a Data Science track since it is a way to satisfy the machine learning requirements.

Data Visualization 

Statistics is also the art of story-telling through the use of data, and what could be better than using graphical visualizations to do so? As the saying goes, A picture is worth a thousand words! STAT 451 is a new class offered by the Statistics Department with the goal of providing students with a comprehensive understanding of data visualization techniques using R. This class requires some computational background (see course catalogue for details on the pre-requisites) and it is geared towards majors and non-majors interested in boosting their data visualization techniques, starting from fundamentals but going all the way to the design and creation of interactive dashboards.