Statistical tools for modern data analysis can be used across a range of industries to help you guide organizational, societal and scientific advances. This course uses industry-standard applications and software (R and Python) for numerical reasoning and predictive data modeling, with an emphasis on conceptual rather than theoretical understanding.
Please note: enrolling in this course for 4 units will require an additional data analysis project.
- Jonathan Taylor Professor, Statistics
- Correlated errors
- Data snooping
- Interactions and qualitative variables
- Multiple linear regression
- Penalized regression
- Regression and prediction
- Simple linear regression
- Variance and cross-validation
Note on Course Availability
The course schedule is displayed for planning purposes – courses can be modified, changed, or cancelled. Course availability will be considered finalized on the first day of open enrollment. For quarterly enrollment dates, please refer to our graduate certificate homepage.
3.0 - 4.0
STATS60, STATS110, or STATS141.