Fall 2024 - HSCI 410 D100
Exploratory Data Analysis (3)
Class Number: 5653
Delivery Method: In Person
Overview
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Course Times + Location:
Sep 4 – Oct 11, 2024: Tue, 8:30–11:20 a.m.
BurnabyOct 16 – Dec 3, 2024: Tue, 8:30–11:20 a.m.
Burnaby -
Exam Times + Location:
Dec 7, 2024
Sat, 12:00–3:00 p.m.
Burnaby
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Instructor:
Joao Luiz Dornelles Bastos
jbastos@sfu.ca
1 778 782-7954
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Prerequisites:
STAT 302 or STAT 305, with a minimum grade of C-. Recommended: HSCI 230.
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 synchronous lecture with hands-on data analysis. There will be three hours of instruction in lecture format with regular class discussion each week.
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 using the R programming language;
● Describe and apply modelling concepts from epidemiology, including interaction, confounding, and summary measures of effect, and what variables to put in your model, and dummy variables;
● Describe common applications of regression in the health sciences;
● Interpret and critically assess reports in the literature and media;
● Apply statistical software for linear and logistic regression models.
Grading
- Group project 40%
- Midterm exam 20%
- Final exam 30%
- Participation 10%
NOTES:
- Group project (groups of 4 or 5 students) term paper using data from the Canadian Community Health Survey (CCHS), with accompanying in-class presentation, which are collectively worth 40% of the final grade.
● 10% for interim report
● 25% for final report.
● 5% for class presentation
- Midterm exam worth 20%: This will be an exam done in the computer that will assess your proficiency in working with the software and doing basic calculations, plots and tables.
- Final exam worth 30%: An exam that will be done in the computer.
- Participation 10%.
REQUIREMENTS:
You must bring a computer to class (e.g., laptop) to run RStudio and analyze health datasets.
Materials
MATERIALS + SUPPLIES:
Canvas will be used as a tool for learning and information exchange in this course. Please, visit http://www.sfu.ca/canvas.html to log into HSCI410 page. Lecture notes, lab materials and assignments will be posted at Canvas site.
REQUIRED READING:
Pagano, Marcello, and Kimberlee Gauvreau. Principles of biostatistics. CRC Press/Taylor & Francis Group, 2018.
ISBN: 978-1-138-59314-5
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.
Registrar Notes:
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
RELIGIOUS ACCOMMODATION
Students with a faith background who may need accommodations during the term are encouraged to assess their needs as soon as possible and review the Multifaith religious accommodations website. The page outlines ways they begin working toward an accommodation and ensure solutions can be reached in a timely fashion.