Data Science W271

Statistical Methods for Discrete Response, Time Series, and Panel Data

3 units

Course Description

A continuation of Data Science W203 (Exploring and Analyzing Data), this course trains data science students to apply more advanced methods from regression analysis and time series models. Central topics include linear regression, causal inference, identification strategies, and a wide-range of time series models that are frequently used by industry professionals. Throughout the course, we emphasize choosing, applying, and implementing statistical techniques to capture key patterns and generate insight from data. Students who successfully complete this course will be able to distinguish between appropriate and inappropriate techniques given the problem under consideration, the data available, and the given timeframe.

Due to the intensive mathematical nature of Data Science W271, students are strongly encouraged to preview the class before registering. Request access to the course preview.

Prerequisites

W203 taken in F2016 or later & completed with a grade of B+ or above; strong hands-on experience in R; working knowledge of calculus & linear algebra; familiarity with differential calculus, integral calculus & matrix notations; or instructor approval.

Course History

Spring 2018

Instructor(s): Jeff Yau
Instructor(s): Jeff Yau

Fall 2017

Instructor(s): Devesh Tiwari
Instructor(s): Jeff Yau
Instructor(s): Devesh Tiwari

Summer 2017

Instructor(s): Devesh Tiwari
Instructor(s): Devesh Tiwari

Spring 2017

Instructor(s): Devesh Tiwari
Instructor(s): Staff

Fall 2016

Instructor(s): Devesh Tiwari, Jeff Yau
Instructor(s): Devesh Tiwari
Instructor(s): Jeff Yau

Summer 2016

Instructor(s): Samuel Frame
Instructor(s): Devesh Tiwari

Spring 2016

Instructor(s): Samuel Frame

Last updated:

January 13, 2017