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15.075 Applied Statistics, Spring 2003

Research and Teaching Output of the MIT Community

Show simple item record Newton, Elizabeth en_US
dc.coverage.temporal Spring 2003 en_US 2003-06
dc.identifier 15.075-Spring2003
dc.identifier local: 15.075
dc.identifier local: IMSCP-MD5-3b7fefac0fd6863a1a5fe7fe205f459f
dc.description.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. en_US
dc.language en-US en_US
dc.relation en_US
dc.rights.uri Usage Restrictions: This site (c) Massachusetts Institute of Technology 2012. Content within individual courses is (c) by the individual authors unless otherwise noted. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license") unless otherwise noted. The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. The Licensor, the Massachusetts Institute of Technology, grants You the rights contained here in consideration of Your acceptance of such terms and conditions. en_US
dc.subject data analysis en_US
dc.subject multiple regression en_US
dc.subject analysis of variance en_US
dc.subject multivariate analysis en_US
dc.subject data mining en_US
dc.subject probability en_US
dc.subject collecting data en_US
dc.subject sampling distributions en_US
dc.subject inference en_US
dc.subject linear regression en_US
dc.subject ANOVA en_US
dc.subject nonparametric methods en_US
dc.subject polls en_US
dc.subject surveys en_US
dc.subject statistics en_US
dc.subject management science en_US
dc.subject finance en_US
dc.subject statistical graphics en_US
dc.subject estimation en_US
dc.subject hypothesis testing en_US
dc.subject logistic regression en_US
dc.subject contingency tables en_US
dc.subject forecasting en_US
dc.subject factor analysis en_US
dc.subject Statistics en_US
dc.title 15.075 Applied Statistics, Spring 2003 en_US
dc.title.alternative Applied Statistics en_US

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