Data Science

Data science is the collection of methods and techniques utilized to appropriately acquire, manipulate, and analyze raw data for the purposes of making impactful decisions and building a better understanding of the world around us. It is a highly interdisciplinary field that combines concepts from statistics, computer science, and mathematics with domain-specific knowledge to extract insightful information from data.

The amount of data being generated and retained has and continues to massively expand as our world becomes increasingly interconnected and digital. This has transformed data into an abundant natural resource that requires skilled data scientists which can ethically and properly process data. This expansion of data and the need for data scientists influences many fields: sports analytics, journalism, marketing, finance, manufacturing, retail, entertainment, energy, medicine, travel and transportation, local and national security, and many more.

The Department of Statistics has 4 courses centered specifically on the application of data science methods and techniques:

  • Data Science 1, 2, & 3 (STAT 301-1, -2, -3) is a series dedicated to building the skills and knowledge necessary to conduct quality data analytics on real data.
  • Data Visualization (STAT 302) is dedicated to building advanced skills and knowledge necessary to appropriately explore and communicate data through visualizations.

For students interested in pursuing a career in Data Science or in a field that relies on data, we recommend taking these courses:

  • STAT 202 Introduction to Statistics*
  • STAT 301-1 Data Science 1
  • STAT 301-2 Data Science 2
  • STAT 301-3 Data Science 3
  • STAT 302 Data Visualization

View the Yearly Course Schedule to see which quarters these STAT courses are offered.

*Please note: STAT 210 Introductory Statistics for the Social Sciences can be substituted for STAT 202 as a prerequisite for STAT 301-1 and STAT 302, but STAT 210 does not include the introduction to using R, a program that features in the Data Science series.

We also suggest taking an additional Statistics course to broaden your understanding of statistics and data science. If you have questions about which courses would be best for your course of study, please contact the Director of Undergraduate Studies, Professor Sandy Zabell, and he will advise you. 


Additional courses in other departments to consider are:

  • An introductory calculus series: MATH 220-0 Differential Calculus of One-Variable Functions and MATH 224-0 Integral Calculus of One-Variable Functions or MATH 212-0 Single Variable Calculus I, MATH 213-0 Single Variable Calculus II, and MATH 214-0 Single Variable Calculus III
  • MATH 230-0 Differential Calculus of Multivariable Functions
  • MATH 234-0 Multiple Integration and Vector Calculus
  • MATH 240-0 Linear Algebra
  • EECS 111: Fundamentals of Computer Programming I
  • IEMS 304: Statistical Learning for Data Analysis
  • IEMS 308: Data Science & Analytics
  • IEMS 351: Optimization Methods in Data Science
  • IEMS 365: Analytics for Social Good