# Spring 2021 - STAT 302 D100

## 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:

One of STAT 201, STAT 203, STAT 205, STAT 270, or BUEC 232.

## Description

#### CALENDAR DESCRIPTION:

The standard techniques of multiple regression analysis, analysis of variance, and analysis of covariance, and their role in observational and experimental studies. This course may not be used to satisfy the upper division requirements of the Statistics major or honours program. Quantitative.

#### COURSE DETAILS:

STAT Workshop Coordinator: Harsha Perera

Outline:

1. Review: Important concepts from the first 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.

Students with Disabilities:
Students requiring accommodations as a result of disability must contact the Centre for Accessible Learning 778-782-3112 or csdo@sfu.ca

Tutor Requests:
Students looking for a Tutor should visit http://www.stat.sfu.ca/teaching/need-a-tutor-.html. We accept no responsibility for the consequences of any actions taken related to tutors.