Spring 2023 - HSCI 410 D100
Exploratory Data Analysis (3)
Class Number: 5646
Delivery Method: In Person
Course Times + Location:
Mo 2:30 PM – 5:20 PM
BLU 9011, Burnaby
Exam Times + Location:
Apr 22, 2023
12:00 PM – 3:00 PM
RCB 8100, Burnaby
1 778 782-8651
Prerequisites:STAT 302 or STAT 305, with a minimum grade of C-. Recommended: HSCI 230.
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.
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.
You must bring a computer to class (e.g. laptop) to run RStudio and analyze health datasets. SFU is not supplying computers for students to use. Alternatively, you may run RStudio and code through a web browser (https://rstudio.cloud/) on your tablet computer or smartphone, although this may lead to a less rewarding experience with computer programming.
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.
- Term paper 50%
- Midterm exam 20%
- Final exam 20%
- Participation 10%
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.
REQUIRED READING NOTES:
Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
SFU’s Academic Integrity website 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