Fall 2023 - PSYC 410 D100

Research Design I (4)

Class Number: 2439

Delivery Method: In Person


  • Course Times + Location:

    Sep 6 – Oct 6, 2023: Tue, 10:30 a.m.–12:20 p.m.

    Oct 11 – Dec 5, 2023: Tue, 10:30 a.m.–12:20 p.m.

    Sep 6 – Dec 5, 2023: Fri, 10:30–11:20 a.m.

  • Instructor:

    Michael Maraun
    1 778 782-5685
    Office: RCB 4202
    Office Hours: Fridays, 12pm - 1pm Though optional, regular participation in the office hours is highly recommended. It is expected that, among other things, students will use this time to discuss matters related to the filmed lectures, the readings, workouts, and assignments. That is to say, anything whatsoever statistical or data analytic is fair game.
  • Prerequisites:

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



Reviews the basic logic of controlled experimentation, and focuses on analysis of variance designs commonly used in psychological research. Particular emphasis is given to the relative merits of the several designs when there are multiple research questions to be answered. Quantitative.


Provisional Structuring of Substantive Areas

PSYC 410/910 is the first in a sequence of two courses- the second being PSYC 411/911- on statistics and data analysis which psychology graduate students take as part of their masters work. The primary focus of 410/910 is on formal experimental design and the analysis data arising from these designs by means of analysis of variance technology, broadly conceived. This material is addressed by means of a consideration of a number of quantitative scenarios, commonly arising in psychology. These scenarios involve manifold components, among them, research design (under which the data that bears on a problem is generated), data analysis, assumption checking, error control, hypothesis testing, and magnitude of effect estimation.


PSYC 410/910 will be comprised of two parts:

i. Fundamentals/background/review
• Data analysis and logic of statistical inference
• Concept of relationship

ii. Selected quantitative scenarios (provisional list)
• 1-way between subject design:
- ANOVA (general relationship question)
- simultaneous inference (set of specific hypotheses)
• 1-way randomized block/repeated measures design and analysis
• p-way between subject design and analysis
• (p+q)-factor mixed design and analysis


  • 4 assignments each worth 10%: 40%
  • 1 midterm: 30%
  • 1 final exam: 30%


A+ 95 and higher
A 90-95
A- 85-90
B+ 80-85
B 75-80
B- 70-75
C+ 65-70
C 60-65
C- 55-60
D 50-55
F less than 50


Components of course

Lectures and lecture notes

Lectures, and the lecture notes on which they are based, are the primary means by which will be covered, the materials of which the course is comprised. The lectures are structured sequentially in accordance with the lecture notes, and proceed through the theoretical materials in a linear fashion, with occasional departures to address computational and output-interpretational issues. The midterm and final are, almost exclusively- Kirk’s chapters on research design being the exception-, based on the lectures. In each lecture, I will be referring directly to the accompanying lecture notes. However, the notes comprise but a sketch. Accordingly, elucidation, fleshing out, and expanding upon will be the standard order of business.

Note: lecture notes will be available on Canvas, in accordance with lecture schedule.


The readings will be drawn primarily, but not exclusively, from the following sources and assigned on an as needed basis.

Kirk, R.E. (1995). Experimental Design: Procedures for the Behavioral Sciences (3rd ed). California; Brooks & Cole.

Myers, J.L, and Well, A.D. (1991). Research Design and Statistical Analysis. New York: HarperCollins Publishers Inc.

With the exception of Kirk, chapters 1 and 2, readings are optional, the express aim in assigning them, to support the coverage provided by the lectures.
Accordingly, aside from Kirk, chapters 1 and 2, which may find their way onto the midterm, you will not be tested directly on readings.
Note: Readings will be available in pdf form on Canvas, in accordance with lecture schedule.


Each of the four assignments will be constituted of either one or two parts, the parts made available to you- on Canvas- as the semester unfolds. A given assignment- all of its parts- will be due- uploaded to Canvas- on the date and time specified on the schedule. The majority of the assignments involve the addressing of empirical questions by means of data and statistical analysis.
Computations may be carried out in either SPSSX or R. When addressing an empirical question by means of data and statistical analysis, your answers must conform to the following structure: i. Introduction; ii. data analysis; iii. statement of statistical hypothesis to be tested; iv. error analysis (power computations and choice of type I error rate); v. assumption checking; vi. outcome of hypothesis test; vii. (wherein necessary) magnitude of effect estimate. The document examplesassign.pdf, available to you in the first module of Canvas, is an assignment from the past which exemplifies this proper structuring.

Midterm and final

There will be one midterm- in class- and one take-home final. You will be able to access the final on Canvas, and will be required to upload your completed exam to Canvas, in accordance with the schedule, below. The final is not cumulative. Neither midterm, nor final, will involve any computation. Both test on the statistical theory on which the course focuses; both are comprised of short essay questions, true and false questions calling for detailed elaboration, etc. You will receive many examples of past midterms and finals, and, once having received these, it is urged that you practice writing out answers. You are encouraged to discuss with me these practice exams, and I will be happy, also, to offer my opinion as to the quality of your written attempts. Traditionally, we spend a lot of office time, in PSYC 410/910, going over peoples’ answers to practice questions.


There will be a number of “workouts”, relatively brief computational/theoretical exercises, each of which we will tackle in the microlab (see schedule). Though it is highly recommended that you complete each and every workout (for they are designed to help you consolidate theoretical knowledge and master practical application), they are not for marks and you will not submit them. Rather, there will be made available to you on Canvas, at the end of the week on which a workout is assigned, an answer key with which, at your leisure, you may compare your answers (and, of course, discuss during office hours).



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:


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


Students with a faith background who may need accommodations during the semester 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.