Introduction to Applied Statistics

STATS191

Stanford School of Humanities and Sciences

  • Fee:
    Fee may apply

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Description

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.

 

Instructor(s)

  • Pratheepa Jeganathan

Prerequisites

Complete STATS202 or STATS216 with a grade of B+ or better.

Topics include

  • Bootstrap
  • Correlated errors
  • Data snooping
  • Interactions and qualitative variables
  • Multiple linear regression
  • Penalized regression
  • Poisson
  • Regression and prediction
  • Simple linear regression
  • Transformations
  • 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.

008 Autumn 2019-20 Online

Enroll Now

Dates:September 23 - December 6, 2019
Days: Mon
Units: 3.00
Instructors: Pratheepa Jeganathan
Delivery Option:
Online
Fees:
For Credit $3,900.00 ?

Notes

Enrollment Dates: August 1 to September 9, 2019

This course may not currently be available to learners in some states and territories.