# Spring 2021 - STAT 604 G100

## Overview

• #### Course Times + Location:

Mo 12:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby

We 12:30 PM – 1:20 PM
REMOTE LEARNING, Burnaby

• #### Exam Times + Location:

Apr 20, 2021
3:30 PM – 6:30 PM
REMOTE LEARNING, Burnaby

• #### Prerequisites:

Any course in Statistics. Open only to students in departments other than Statistics and Actuarial Science.

## Description

#### CALENDAR DESCRIPTION:

The standard techniques of multiple regression analysis, analysis of variance, and analysis of covariance, and their role in experimental research. Students with credit for STAT 302 may not take this course for further credit.

#### COURSE DETAILS:

STAT Workshop Coordinator: Harsha Perera

Outline:

1. Review: Important concepts from the irst course in statistics will be reviewed.
2. Simple linear regression (SLR): models summarizing the relationship between two quantitative variables. This includes the estimation and interpretation of model parameters, assessment of the model’s it, inference, and prediction.
3. Multiple regression: constructing models in which several explanatory variables combine to help explain the variability in a quantitative response variable. This includes model assessment, comparison of two regression lines, interactions between explanatory variables, and multicollinearity. Additional topics may include identifying unusual points, variable selection, and/or coding categorical predictors.
4. Analysis of variance (ANOVA): Use of models to compare means of a quantitative response variable between groups de ined by a categorical explanatory variable (e.g. a treatment variable). Includes model assessment and inference for comparison of means. If time allows, other topics in ANOVA may be included, such as analysis of covariance, tests for homogeneity of variances, the problem of multiple testing, and/or block designs.

Mode of teaching:

• Lecture: synchonous (recorded)
• Tutorials:synchronous (recorded, with scheduled bi-weekly quizzes)
• Midterms: NA
• Final exam: synchronous; date: TBA
• Remote invigilation: Zoom will be used.

• Quizzes (best 5 out of 6) 65%
• Final Exam 35%

#### NOTES:

You must pass the final exam to pass the course.

Above grading is subject to change.

## Materials

#### MATERIALS + SUPPLIES:

STAT2 Modeling with Regression and ANOVA, 2nd ed. by Cannon, Cobb, Hartlaub, et al. Publisher: Macmillan Learning

There may be an e-version of the textbook available, please check the Canvas course for details.

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.