Description
Linear regression - theory, methods and application(s). Normal distribution theory. Hypothesis tests and confidence intervals. Model selection. Model diagnostics. Introduction to weighted least squares and generalized linear models.
Prerequisites
- Prerequisite(s): i) STAT 2559 with a grade of C- or higher, or STAT 2210 with a grade of C or higher; and ii) a grade of C- or higher in MATH 1152 or MATH 1107 or MATH 1104 ; or permission from the School of Mathematics and Statistics.
Conditions and arrangements
- Precludes additional credit for Precludes additional credit for STAT 3503 .
- Prerequisite(s): i) STAT 2559 with a grade of C- or higher, or STAT 2210 with a grade of C or higher; and ii) a grade of C- or higher in MATH 1152 or MATH 1107 or MATH 1104 ; or permission from the School of Mathematics and Statistics.
- Lectures three hours a week, laboratory one hour a week.
Reference text in its original language
Linear regression - theory, methods and application(s). Normal distribution theory. Hypothesis tests and confidence intervals. Model selection. Model diagnostics. Introduction to weighted least squares and generalized linear models.
- Prerequisite(s): i) STAT 2559 with a grade of C- or higher, or STAT 2210 with a grade of C or higher; and ii) a grade of C- or higher in MATH 1152 or MATH 1107 or MATH 1104 ; or permission from the School of Mathematics and Statistics.
- Precludes additional credit for Precludes additional credit for STAT 3503 .
- Lectures three hours a week, laboratory one hour a week.
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/