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STAT 306 - Department of Statistics - University of British Columbia

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<strong>University</strong> <strong>of</strong> <strong>British</strong> <strong>Columbia</strong>, <strong>Department</strong> <strong>of</strong> <strong>Statistics</strong><strong>STAT</strong> <strong>306</strong> Finding Relationships in Data2012-2013 Term 2_______________________________________________________________________DescriptionInstructorOffice hoursClass place/timeCourse web pageCourse textModeling a response (output) variable as a function <strong>of</strong> severalexplanatory (input) variables: multiple regression for a continuousresponse and logistic regression for a binary response. Findinglow-dimensional structure: principal components analysis, clusteranalysis.Term 2: Yew-Wei LimTBALecture: Tues and Thurs, 9:30am -11:00am.Term 2: Earth Sciences Building 1012TBACourse notes (from UBC Bookstore)Prerequisite One <strong>of</strong> MATH 152, MATH 221, MATH 223 and one <strong>of</strong> <strong>STAT</strong> 200,<strong>STAT</strong> 241, <strong>STAT</strong> 251, BIOL 300 and one <strong>of</strong> MATH 302, <strong>STAT</strong> 302.Co-requisiteCredit exclusionNoneConsult the Credit Exclusion list within the Faculty <strong>of</strong> Sciencesection in the calendar.<strong>STAT</strong> <strong>306</strong> COURSE OUTLINEPart 1:- Simple linear regression: least squares- Basic probability : expectation, variance, covariance- Multiple regression: regression in matrix notation, least squares estimation, inferencefor regression parameters, categorical predictors, transformations- Residual analysis and model diagnostics- Variable selection: stepwise methods, cross-validation


Part 2: (some topics from list below)- Logistic regression for binary data- Principal components analysis- Cluster analysisYL/es Date <strong>of</strong> last revision: 2012/20132

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