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15.075 Applied Statistics, Spring 2003

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dc.contributor.author Newton, Elizabeth
dc.coverage.temporal Spring 2003
dc.date.accessioned 2012-09-14T09:27:00Z
dc.date.available 2012-09-14T09:27:00Z
dc.date.issued 2003-06
dc.identifier 15.075-Spring2003
dc.identifier.other 15.075
dc.identifier.other IMSCP-MD5-3b7fefac0fd6863a1a5fe7fe205f459f
dc.identifier.uri http://hdl.handle.net/1721.1/72947
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
dc.language.iso en-US
dc.relation.hasversion http://www.core.org.cn/OcwWeb/Sloan-School-of-Management/15-075Applied-StatisticsSpring2003/CourseHome/index.htm
dc.rights 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
dc.subject data analysis en
dc.subject multiple regression en
dc.subject analysis of variance en
dc.subject multivariate analysis en
dc.subject data mining en
dc.subject probability en
dc.subject collecting data en
dc.subject sampling distributions en
dc.subject inference en
dc.subject linear regression en
dc.subject ANOVA en
dc.subject nonparametric methods en
dc.subject polls en
dc.subject surveys en
dc.subject statistics en
dc.subject management science en
dc.subject finance en
dc.subject statistical graphics en
dc.subject estimation en
dc.subject hypothesis testing en
dc.subject logistic regression en
dc.subject contingency tables en
dc.subject forecasting en
dc.subject factor analysis en
dc.subject.lcsh Statistics en
dc.title 15.075 Applied Statistics, Spring 2003 en
dc.title.alternative Applied Statistics en
dc.audience.educationlevel Undergraduate
dc.subject.cip 270502 en
dc.subject.cip Mathematical Statistics and Probability en
dc.date.updated 2012-09-14T09:27:01Z


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