# Spring 2021 - STAT 605 G100

## Overview

• #### Course Times + Location:

Mo 2:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby

We 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby

• #### Exam Times + Location:

Apr 17, 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:

Intermediate statistical techniques for the health sciences. Review of introductory concepts in statistics and probability including hypothesis testing, estimation and confidence intervals for means and proportions. Contingency tables and the analysis of multiple 2x2 tables. Correlation and regression. Multiple regression and model selection. Logistic regression and odds ratios. Basic concepts in survival analysis. Students with credit for STAT 305 may not take this course for further credit.

#### COURSE DETAILS:

STAT Workshop Coordinator: Harsha Perera

Course Details:
Synchronous and online.

Course Outline:

This graduate course provides an opportunity for the further development of analytic skills acquired in basic courses in statistics and the health sciences. It concentrates on the relatively few techniques that are currently most used in health research, but it also seeks to provide a conceptual basis for understanding other techniques. The course focuses on unifying principles and widely applicable methods as opposed rote memorization of an array of unrelated ad-hoc procedures. The material is presented descriptively, from the point of view of understanding and practical use.

The emphasis of the course is on analysis (rather than design) of observational studies where there is one outcome variable of primary interest and where the data are made up of multiple independent observations. Important areas not covered are: classical multivariate analysis (e.g., factor analysis, discriminant analysis, etc.), longitudinal data analysis, time series, random effects models, and experimental design considerations (e.g., Latin squares, etc.).

Objectives:

By the end of the course the participant should:

1. understand the concept of a statistical model and how such models correspond to specific hypotheses or questions,
2. be able to interpret the results of an analysis in relation to the original questions or hypotheses that motivated the analysis,
3. be familiar with data analysis methods commonly used in health sciences and understand the basic limitations of competing methods,
4. understand and be able to critique the analysis methods described in published health research papers,
5. be able to communicate effectively with statistical consultants.

Topics:

The scheduling of the following topics is approximate:

1. Review of introductory statistics from the pre-requisite course: Hypothesis testing, estimation and confidence intervals for means and proportions.
2. Review of basic concepts of probability with applications including diagnostic testing, sensitivity and specificity, the relative risk and the odds ratio.
3. Contingency Tables: The Chi-square test, r x c tables, multiple 2x2 tables, Simpson's paradox, Mantel- Haenszel method.
4. Correlation and simple linear regression: Regression concepts, estimation and testing for regression coefficients, evaluation of the model.
5. Multiple linear regression: Inference for regression coefficients, confounding and interaction, indicator variables, model selection, prediction, model assumptions and checking.
6. Logistic regression: Odds ratios, inference for regression coefficients, model assumptions, case-control studies.
7. Time permitting: Survival analysis including life tables, censoring, Kaplan-Meier method, log-rank test.

Mode of teaching:

• Lectures (and Quizzes) - MIX of Asynchronous and Synchronous
• Midterm: Synchronous
• Final exam: Synchronous
• Remote invigilation (Zoom, Proctorio, or other approved software) will be used

• Quizzes/HW Assignments 35%
• Midterm Exam (in scheduled class meeting times) 30%
• Final Exam (in scheduled class meeting times) 35%

#### NOTES:

There will be no make-up midterms.

Above grading is subject to change.

#### REQUIREMENTS:

Student participation in this course will require computer equipment and a reliable internet connection. You may be requested to turn on audio and/or video during certain instructional activities, that may include tests and examinations, though exceptions will be accommodated. If you request such an exception for personal reasons, you must do so in writing to the course instructor by the end of the first week.

Tech Requirements for online course STAT 305/605:

To be able to complete the online class successfully, at a minimum you will need a personal computer, access to the internet, a webcam, and a microphone to take online exams.

Zoom will be used to proctor the exams.

## Materials

#### MATERIALS + SUPPLIES:

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.