Spring 2019 - GERO 803 G100
Analytical Techniques for Gerontological Research (4)
Class Number: 6989
Delivery Method: In Person
Overview
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Course Times + Location:
Jan 3 – Apr 8, 2019: Wed, 9:30 a.m.–12:20 p.m.
Vancouver
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Instructor:
Zheng Wu
z_wu@sfu.ca
Description
CALENDAR DESCRIPTION:
This course has been specifically designed to provide training in quantitative data analysis using SPSSx Programming Language with a focus on behavioral research problems in gerontology.
COURSE DETAILS:
The purpose of the course is to provide class participants with a working understanding of ordinary least squares (OLS) techniques. We will also extend this knowledge to incorporate models which are commonly subsumed in the framework of the general linear model.
The course begins with a review of basic concepts in statistics, such as sampling distribution and statistical inference, and selected topics in bivariate statistics. Then we extend this discussion to that of bivariate and multivariate relationships. Our emphasis will be on multiple regression techniques, including a discussion of dummy variables, statistical interaction, missing data problems and the assumptions made in ordinary least squares estimation (e.g., linearity, collinearity, normality, outliers, and influential observations), diagnostic techniques, and remedial methods. If time permits, we will also introduce models with binary dependent variables.
COURSE-LEVEL EDUCATIONAL GOALS:
The objective of the course is to provide students with a working knowledge of some basic statistical tools that they can use in writing research papers and completing their thesis (dissertation) work that involve analyzing quantitative data.
Grading
- Mid term 25%
- Assignments 40%
- Final exam 35%
NOTES:
COMPUTER REQUIREMENTS:
The course will be structured around R as the main statistical package. A brief introduction to the package will be given in class.
REQUIREMENTS:
There are two exams covering the material from the lectures and assigned readings. The midterm, which accounts for 25% of your final grade, covers the material from the beginning of
the term. The final exam includes the material from the entire course and accounts for 35% of your final grade. For each exam, you are permitted to bring a hand calculator and one 8 1/2 by 11 inch sheet on which you may write anything. You may use both sides. But it must be in your own handwriting and not a photocopy.
There are 3 computer-based assignments. They are worth 10%, 10% and 20%, respectively. The first two assignments involve some computer exercises and a brief write-up. The third assignment is a mini-research paper (note). The objective is to apply one or more of the statistical methods taught in the course to a substantive research area of your choice with a real dataset. A brief (decent) literature review, theoretical argument(s), and empirical evidence are all important. Ideally, students can bring a dataset to the course so that statistical methods taught can be applied to the analysis of the data.
Materials
MATERIALS + SUPPLIES:
An inexpensive scientific calculator is needed.
REQUIRED READING:
1. An R Companion to Applied Regression. 2010. Fox, John and Weisberg, Harvey.
2. Applied Regression Analysis and Generalized Linear Models, 2015. Fox, John
Graduate Studies Notes:
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.
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