Statistics for Data Science

The goal of this course is to provide students with an introduction to many different types of quantitative research methods and statistical techniques for analyzing data. We begin with a focus on measurement, inferential statistics and causal inference using the open-source statistics language, R. Topics in quantitative techniques include: descriptive and inferential statistics, sampling, experimental design, tests of difference, ordinary least squares regression, general linear models.

Skill Sets

Research design / Statistical analysis

Tools

R

Current Course Designers

Paul Laskowski

Associate Adjunct Professor
Alumni (PhD 2009)

paul@ischool.berkeley.edu

Website

D. Alex Hughes

Assistant Adjunct Professor

d.alex.hughes@ischool.berkeley.edu

305B South Hall

Website

Original Course Designer

Coye Cheshire

Professor

coye@ischool.berkeley.edu

305A South Hall

Website

(510) 643-6388

Course must be taken for a letter grade to fulfill degree requirements.

Previously listed as DATASCI W203. Prior to Fall 2016, the course was titled “Exploring and Analyzing Data.”