15.075 Applied Statistics, Spring 2003

Newton, Elizabeth

Author(s)

Newton, Elizabeth

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Alternative title

Applied Statistics

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Abstract

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.

Date issued

2003-06

URI

http://hdl.handle.net/1721.1/72947

Department

Sloan School of Management

Other identifiers

15.075-Spring2003

local: 15.075

local: IMSCP-MD5-3b7fefac0fd6863a1a5fe7fe205f459f

Keywords

data analysis, multiple regression, analysis of variance, multivariate analysis, data mining, probability, collecting data, sampling distributions, inference, linear regression, ANOVA, nonparametric methods, polls, surveys, statistics, management science, finance, statistical graphics, estimation, hypothesis testing, logistic regression, contingency tables, forecasting, factor analysis, Statistics

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