Spring 2020 - HSCI 410 D100

Exploratory Data Analysis (3)

Class Number: 2181

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 6 – Apr 9, 2020: Thu, 11:30 a.m.–2:20 p.m.
    Burnaby

  • Exam Times + Location:

    Apr 15, 2020
    Wed, 12:00–3:00 p.m.
    Burnaby

  • Prerequisites:

    STAT 302 or STAT 305. Recommended: HSCI 330.

Description

CALENDAR DESCRIPTION:

Regression and data analysis techniques for health research. Practical approaches to linear and logistic regression, multivariable modelling, interaction, variable selection, confounding, and measures of association. Computer-based laboratory exercises using statistical software applied to health datasets.

COURSE DETAILS:

A single three hour lecture in the computer lab with hands on data analysis. Each week there will be three hours of instruction in lecture format with regular class discussion.

COURSE-LEVEL EDUCATIONAL GOALS:

At the end of this course, students should be able to:

  • Describe the basic concepts in linear and logistic regression modelling
  • Describe and apply modelling concepts from epidemiology including interaction, confounding and summary measures of effect, and what variables to put in your model.
  • Describe common applications of regression in the health sciences
  • Be able to interpret and critically assess reports in the literature and media
  • Apply statistical software for linear and logistic regression models.

Grading

  • Term paper 50%
  • Midterm exam 20%
  • Final exam 20%
  • Participation 10%

Materials

REQUIRED READING:

Required Textbook:

Principles of Biostatistics, Marcello Pagano and Kimberlee Gauvreau, 2nd Ed. A copy of the textbook is on reserve that the SFU library. The textbook is required and examinations are open book.

Registrar Notes:

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS