Description
Review of simple and multiple regression with matrices, Gauss-Markov theorem, polynomial regression, indicator variables, residual analysis, weighted least squares, variable selection techniques, nonlinear regression, correlation analysis and autocorrelation. Computer packages are used for statistical analyses.
Prerequisites
- Prerequisite(s): i) DATA 1519 or STAT 2509 or STAT 2602 or STAT 2607 or ECON 2202 or ECON 2220 or equivalent; and ii) MATH 1152 or MATH 1107 or MATH 1119 or equivalent; or permission of the School.
Conditions and arrangements
- Precludes additional credit for Precludes additional credit for STAT 3553 .
- Prerequisite(s): i) DATA 1519 or STAT 2509 or STAT 2602 or STAT 2607 or ECON 2202 or ECON 2220 or equivalent; and ii) MATH 1152 or MATH 1107 or MATH 1119 or equivalent; or permission of the School.
- Lectures three hours a week and one hour laboratory.
Reference text in its original language
Review of simple and multiple regression with matrices, Gauss-Markov theorem, polynomial regression, indicator variables, residual analysis, weighted least squares, variable selection techniques, nonlinear regression, correlation analysis and autocorrelation. Computer packages are used for statistical analyses.
- Prerequisite(s): i) DATA 1519 or STAT 2509 or STAT 2602 or STAT 2607 or ECON 2202 or ECON 2220 or equivalent; and ii) MATH 1152 or MATH 1107 or MATH 1119 or equivalent; or permission of the School.
- Precludes additional credit for Precludes additional credit for STAT 3553 .
- Lectures three hours a week and one hour laboratory.
Sources and references
Dates and sources are retained to help you verify the information. Translations are provided to facilitate reading; the official source governs conditions and requirements.
Source reference : https://calendar.carleton.ca/undergrad/courses/STAT/