Introduction to Applied Statistics
Fee may apply
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.
- Pratheepa Jeganathan
- 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
This course is typically offered Autumn quarter.
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.
|Dates:||September 23 - December 6, 2019|
Provides Stanford University credit that may later be applied towards a graduate degree or certificate. Includes access to online course materials and videos for the duration of the academic quarter. Starting Autumn 2016 there is a $100 fee per course for courses dropped before the drop deadline. Click here for more information about our Registration Policies.
NotesEnrollment Dates: August 1 to September 9, 2019
This course may not currently be available to learners in some states and territories.