ILR students who matriculate in fall 2024 and beyond must complete 7 total credits from the ILR Statistics Requirement List below. Students who matriculate between fall 2022 and spring 2024 should follow the prescribed sequences on the Fall 2022 and Beyond Curriculum page.

Be sure to check that you have completed the necessary pre-requisites prior to signing up for a course. Not all courses have the same number of credits. You can follow a suggested sequence or choose 7 total credits of your choosing.

ILR Statistics Requirement List

  • ILRST 2100 Introductory Statistics and Data Science
  • ILRST 2110 Statistics Methods for the Social Sciences II
  • ILRST 2130 Applied Regression Analysis
  • ILRST/ECON/STSCI 3110 Probability Models and Inference for the Social Sciences
  • ILRST/INFO/STSCI 3900 Causal Inference
  • CS 1110 Introduction to Computing: A Design and Development Perspective
  • CS 1112 Introduction to Computing: An Engineering and Science Perspective
  • ECON 3120 Applied Econometrics
  • INFO 1260 Choices and Consequences in Computing
  • INFO 2950 Introduction to Data Science
  • STSCI 1380 Data Science for All
  • STSCI 2120 Introduction to R Programming
  • STSCI 3040 R Programming for Data Science
  • STSCI 3600 Integrated Ethics in Data Science
  • STSCI/BTRY 4030 (STSCI 5030) Linear Models with Matrices

Suggested Sequences

  • Statistics in the Social Sciences
    • Introductory Statistics and Data Science - ILRST 2100 - 4 credits OR Data Science for All - STSCI 1380 - 4 credits
    • Statistical Methods for the Social Sciences II - ILRST 2110 - 3 credits OR Causal Inference - ILRST/INFO/STSCI 3900 - 3 credits
  • Probability and Econometrics
    • Probability Models and Inference for the Social Sciences - ECON/ILRST/STSCI 3110 - 4 credits
    • Applied Econometrics - ECON 3120 - 4 credits
  • Statistics and Data Science
    • Introductory Statistics and Data Science - ILRST 2100 - 4 credits OR Data Science for All - STSCI 1380 - 4 credits
    • Applied Regression Analysis - ILRST 2130 - 2 credits
    • One additional course with a substantial data science/analytic component chosen from the list below
      • Choices and Consequences in Computing - INFO 1260 - 3 credits
      • Causal Inference - ILRST/INFO/STSCI 3900 - 3 credits
      • Introduction to Data Science - INFO 2950 - 4 credits
      • Integrated Ethics in Data Science - STSCI 3600 - 3 credits
      • R Programming for Data Science - STSCI 3040 - 4 credits
  • Programming and Data Science I
    • Introduction to R Programming - STSCI 2120 - 2 credits
    • Probability Models and Inference for the Social Sciences - ECON/ILRST/STSCI 3110 - 4 credits OR Data Science for All - STSCI 1380 - 4 credits
    • One additional programming course chosen from the list below
      • Applied Regression Analysis - ILRST 2130 - 2 credits
      • Causal Inference - ILRST/INFO/STSCI 3900 - 3 credits
      • Choices and Consequences in Computing - INFO 1260 - 3 credits
      • Introduction to Data Science - INFO 2950 - 4 credits
      • Integrated Ethics in Data Science - STSCI 3600 - 3 credits
      • R Programming for Data Science - STSCI 3040 - 4 credits
  • Programming and Data Science II
    • Introduction to Computing: A Design and Development Perspective - CS 1110 - 4 credits OR Introduction to Computing: An Engineering and Science Perspective - CS 1112 - 4 credits
    • One additional course chosen from the list below
      • Probability Models and Inference for the Social Sciences - ECON/ILRST/STSCI 3110 - 4 credits
      • Data Science for All - STSCI 1380 - 4 credits
      • Causal Inference - ILRST/INFO/STSCI 3900 - 3 credits