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Applied Statistics

As taught in: Spring 2003

Image comparing statistics and probability.

Diagram showing the difference between statistics and probability. (Image by MIT OpenCourseWare. Based on Gilbert, Norma. Statistics. W.B. Saunders Co., 1976.)


Dr. Elizabeth Newton

MIT Course Number:




Course Features

Course Description

This course is an introduction to applied statistics and data analysis. Topics include collecting and exploring data, basic inference, simple and multiple linear regression, analysis of variance, nonparametric methods, and statistical computing. It is not a course in mathematical statistics, but provides a balance between statistical theory and application. Prerequisites are calculus, probability, and linear algebra.

We would like to acknowledge the contributions that Prof. Roy Welsch (MIT), Prof. Gordon Kaufman (MIT), Prof. Jacqueline Telford (Johns Hopkins University), and Prof. Ramón León (University of Tennessee) have made to the course material.

*Some translations represent previous versions of courses.