With the rise of easy data access and the reduced cost of computing, everyone can obtain data and report "stats." But to make sense of the numbers one needs to follow solid statistical methods and practices. ILR is a partner in Cornell's Department of Statistics and Data Science, which offers courses in statistics, application of statistical methods, and supervision for students across Cornell University. Our courses range from introductory statistics to advanced statistical techniques that train students in proper methods.
Meeting the ILR Statistics Requirements
- Take Introduction to Statistics, ILRST2100. This four-credit class is offered every semester. Students start with the basics of data collection and end with the application of hypothesis testing for regression models. We recommend that you take the introduction to statistics course (ILRST2100) early in your ILR education.
- Students interested in the Economics minor or more advance statistical methodology should take Probability Models and Inference for the Social Sciences, ILRST3110 rather than ILRST 2100. This four-credit class is offered every semester. This course requires introductory calculus and prepares students for further work in econometrics.
- Transfer your non-ILR statistics course into ILR, either from another Cornell college or outside of Cornell. You will need to provide the syllabus, book information, and details on the content covered. If your transfer course meets some but not all of the requirements, then we may ask you to take an additional two-credit class. Contact the ILR Registrar for evaluation of materials.
- AP Statistics credit. If you have taken the AP Statistics exam and received a 4 or 5 then you have satisfied the undergraduate requirement. Submit AP records for evaluation to the ILR Registrar. You are strongly urged talk with a department member to learn about additional courses in statistics at Cornell.
Master's ILR Graduate Students
- Take Statistical Methods for the Social Science course, ILRST5110. This three-credit class is offered every semester. Students are assumed to have had a prior statistics course at the level of ILRST 2100 and are ready to apply statistical reasoning and techniques to a wide variety of datasets. [Note that this course is under revision.]
- Waive the requirement with at least three semesters of undergraduate coursework in statistics including multiple regression and ANOVA. Contact the ILR Registrar for evaluation of materials.
Non-ILR Students Looking for Introductory courses – See Department of Statistical Science for course options.
Recommended Additional Methodology Courses
- Statistical Methods for Social Science – ILRST2110
- Statistical Sampling – ILRST3100
- Categorical Data Analysis – ILRST4110
- Survival Data Analysis – ILRST4270
- Human Resource Analytics – ILRHR4664
- Introduction to Python Programming – CS1110
- Data Science for All – STSCI 1380
Courses of Study
See course schedules and descriptions for undergraduate and graduate students.