Statistics & Data Science at Yale University

Statistics & Data Science at Yale University

When I entered my first data science class at Yale University, I had no idea what Data Science was. Having gone to a large public school with limited computer science available, data science was completely foreign to me. For those who are unfamiliar with the field of data science, data science is a field of study that merges research, programming, and statistical analyses to extract analyses from data. Statistics and Data Science became a major at Yale in 2017, and Yale prides itself on being one of the first universities across the country to offer a major with a Data Science component in the name. 

Major Admission Process and Strengths 

To major in Statistics and Data Science at Yale, there is no application process for the major. A prerequisite before being admitted into the major, however, is MATH 120: Calculations of Functions in Multiple Variables. At my high school, the highest math course offered was AP Calculus BC, which is the equivalent of MATH 115 at Yale. Hence, I took Math 120 in my sophomore year at Yale. The Statistics and Data Science major challenges students to take two or more courses in each of the following fields: core probability and statistics, computational skills, and methods of data science. The Statistics and Data Science program also encourages students who want to pursue programming in their career to take courses in efficient computation and big data, though no courses in this field are required to graduate with the major. 

A strength of the major is that the major’s course offerings are highly interdisciplinary; many of the courses offered share content with other majors, including, but not limited to Political Science, Physics, Economics, and Molecular, Cellular, and Developmental Biology (MCDB). The Bachelor of Arts degree requires 11-course credits while the Bachelor of Science degree in Data Science requires 14-course credits. The major is completed with the submission of a capstone course or an individual research course in senior year. Another strength of the major is the applicability of the curriculum to the professional skills required of the competitive contemporary data science job market as the major emphasizes real-world applications to statistical theory.

A sample major timeline is as follows: 

• First Year Fall: S&DS 106: Introduction to Statistics, MATH 115: Calculus of Functions in One Variable
• First-Year Spring: MATH 120: Calculations of Functions of Several Variables, S&DS 238: Probability and Statistics
• Sophomore Year Fall: MATH 225: Linear Algebra, S&DS 242: Theory of Statistics
• Sophomore Year Spring: S&DS 230: Data Exploration and Analysis, CPSC 100: Introduction to Computing and Programming 
• Junior Year Fall: S&DS 312: Linear Models, S&DS 363: Multivariate Statistics for the Social Sciences
• Junior Year Spring: CPSC 223: Data Structures and Programming Techniques, PLSC 349: Visualization of Political and Social Data
• Senior Year Fall: YData: Data Science for Political Campaigns, Senior Capstone Project 

By taking 1-2 courses in Data Science each semester, you will have ample space in your schedule to utilize the 1-2 remaining courses in your course load to double major or pursue a certificate (Yale’s equivalent of a minor) in another field of study.

My Experience in the Statistics and Data Science Major at Yale

My favorite class that I’ve taken in the Statistics and Data Science department at Yale is S&DS 176: Data Science for Political Campaigns, which I took in my sophomore year at Yale. Despite having limited experience programming in Python (all of the courses I had taken previously at Yale were conducted in the programming language R), the professor, Joshua Kalla, was incredibly helpful and encouraging in helping me learn the ropes of Python. By the end of the semester, I was able to build a rudimentary predictive voting model, which I expanded upon in a later course PHYS 378: Scientific Computing, when I built a feature model that found which factors were most important to voting decisions in the 2020 election at the county level. Since Yale is on the East Coast and Yale Law School is integrated into campus, studying political science has been an integral part of my Yale experience and I’ve been able to pursue Statistics and Data Science while prioritizing my interest to learn more about government and politics.

Although the major may seem daunting at first, through attending office hours tutoring, and by embellishing your understanding by working with peers, studying Statistics and Data Science becomes exciting and doable. My experience with machine learning classes at Yale allowed me to secure an internship this upcoming summer as a Data Science Consultant for a hospital in Southern California and a research assistant position investigating corruption within the Mexican government. If you want to have skills that are widely applicable and be at the cutting edge of information technology research in your field of study, I highly recommend the Statistics and Data Science major at Yale. 

Written by Vivian Vasquez, PathIvy Yale University Ambassador