Introduction to Applied Statistics
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.
- 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.
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