Spring 2021 - PSYC 411 D100

Research Design II (4)

Class Number: 2018

Delivery Method: Remote


  • Course Times + Location:

    Th 2:30 PM – 5:20 PM

  • Prerequisites:

    PSYC 201, 210, 301, 60 units, and a CGPA of 3.0. Recommended: PSYC 410.



Focuses on multivariate regression and correlation models. Deals with ways of answering questions when direct experimental manipulation is not feasible, and demonstrates the utility of the principles involved for solving problems other than those for which they were first proposed.. Quantitative.


Psyc 411/911
A survey of the concepts and mathematics essential to an understanding of the multivariate analytic techniques employed in psycological research, with special reference to bivariate association. Overview of fundamental data screening and assumption checking procedures. Focus on multivariate regression and correlation models.

This course will be taught remotely due to COVID-19 primarily using SYNCHRONOUS teaching strategies during scheduled class time; Lecture/seminar/group discussions and group office hours will be recorded and available on Canvas. Some lectures may involve ASYNCHRONOUS components with selected podcast episodes and/or PPT lectures.

Remote attendance is required.

REQUIRED TECHNOLOGY: To participate in this class you MUST have reliable internet and a computing device with audio-capacity (to speak/to listen) with the ability to access Canvas BB Collaborate and Zoom. Having ability to have audio on during class discussions is required; having video on is optional. We will be using a combination of Canvas tools, BB Collaborate and Zoom, and google tools (e.g., docs/slides/forms) as necessary.


-Students will increase their knowledge and skill in the framing and addressing research questions using correlational and regression analysis strategies.

-Students will increase their knowledge and skill in study design, data analysis, and communication of research plans and research findings.


  • Tentative Grading: * This course involves a series of ungraded and graded activities over the course of the term. There will be 4 Primary Graded assignments on which course grades will be based:
  • Assignment 1: 20%
  • Assignment 2: 25%
  • Assignment 3: 25%
  • Assignment 4: 30%


Tentative Structure : Psyc411/911 will be comprised of three parts, with primary emphasis on Parts II and III.

Part I. Review of Fundamentals/background;
-Planning research, Data analysis, Logic of statistical inference
-Fundamentals of importance of assumptions and assumption checking and other diagnostics, Type I error control, power, missing data
-Introduction to research scenarios and questions appropriate for multivariate correlation and regression analysis

II. Designs and research questions addressed with Bivariate and Multivariate correlation research questions and analyses
- assumptions and assumption checking/diagnostics
- Type I error control, power
- basic analyses involving a single bivariate correlation
- comparisons between two or more independent correlations (between group comparisons)
- modeling patterns within a correlation matrix;
- comparisons between two or more dependent correlations (within group comparisons)

III. Designs and research questions addressed with ordinary least squares
multiple regression analysis
- assumptions and assumption checking/diagnostics
- Type I error control, power
- single predictor and multiple predictor models (quantitative predictors)
- curvilinear models
- models including interaction terms among quantitative predictors
- models with categorical variables as predictor variable
- models with interaction terms between categorical and continuous
- ANCOVA as a special case of multiple regression

Brief contrast of the following methods to OLS multiple regression analysis will be made, however, coverage of the following will not be deep.
- Logistic Regression Analysis
- Weighted Least Squares Regression Analysis
- Poisson Regression Analysis



Hand or on-line calculator, access to SPSS or R


Select chapters will be assigned from:
Myers, J.L, Well, A.D., & Lorch Jr., R.F. (2010). Research Design and Statistical Analysis. New York: Routledge Press.
Supplementatl readings will be announced/assigned as appropriate.

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


Teaching at SFU in spring 2021 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.

Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112).