Fall 2020 - PSYC 910 G100

Research Design I: Experiments (3)

Class Number: 3118

Delivery Method: In Person

Overview

  • Course Times + Location:

    Tu 2:30 PM – 4:20 PM
    REMOTE LEARNING, Burnaby

    Th 2:30 PM – 3:20 PM
    REMOTE LEARNING, Burnaby

  • Exam Times + Location:

    Dec 19, 2020
    7:00 PM – 10:00 PM
    REMOTE LEARNING, Burnaby

Description

CALENDAR DESCRIPTION:

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.

COURSE DETAILS:

Provisional Structuring of Substantive Areas

Psyc410/910 is the first in a sequence of two courses- the second being psyc411/911- 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 their analysis 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.

Psyc410/910 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

Grading

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

NOTES:

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. This year, due to Covid, lectures will be filmed and made available to you, along with the accompanying pdf lecture notes- both, on Canvas-, at the beginning of each week. 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. Once a filmed lecture is “released”, you will be able to return to it, and view it, throughout the semester.

Assignments
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 on the date and time specified on the schedule, below. Computations may be carried out in either SPSSX or R. You are free to download either one or both of these programs (SPSS is available from SFU, it services; R, online from Cran). There will be made available to you, in the first week, as a reading, a properly executed assignment from the past. You will see, in particular, that this assignment is properly structured as follows: 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.

Midterm and final
There will be one midterm and one final, each of which- due to the Covid situation- you will undertake at home. You will be able to access each, and will be required to upload your finished exam, 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 free to ask me for my opinion as to the quality of an answer. Traditionally, we spend a lot of office time, in psyc410/910, going over peoples’ answers to practice exams. I’d like to mimic this process in the virtual mode, as felicitously as possible. To this end, I urge that you take opportunity to discuss practice midterms and finals in synchronous office hours and, asynchronously, as discussions items on Canvas.

Workouts
There will be a number of “workouts”, relatively brief computational/theoretical exercises, each of which you will undertake on your own and in accordance with
your own 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 will not be submitted. Rather, there will be made available to you, at the end of the week
on which a workout is assigned, an answer key. You may compare your answers to the answer key at your leisure (and, of course, discuss during office hours).

Office hours
There will be weekly office hours, held synchronously (see schedule, below), using the Zoom web conferencing app. 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.

Canvas Discussions
The text-based discussion feature of SFU’s Canvas platform will offer students the opportunity to post questions and comments, and me, the opportunity to answer, clear up confusions, etc. I will do my best to address questions and comments in a timely fashion.

Recapitulation of implications of the university’s response to Covid: The course will be, in the main, offered in a virtual and asynchronous format. There is, of course, the necessity, in a statistics course, of discussing lecture and reading material, and, accordingly, of scheduling some synchronous class time. The synchronous class time that will take place this semester is a weekly, optional (but highly recommended), office hours (see schedule, below), to be held using the Zoom web conferencing app. The following is a compact recapitulation of the implications for each component of the course:

lectures: Asynchronous. I will film lectures and make them available to you- on Canvas- at the beginning of each week (see schedule, below). Once a lecture is made available, you will be able to view it, and return to it, throughout the semester.
readings: Asynchronous. When there are readings, they will be made available to you in pdf form- on Canvas- at the beginning of the week on which they bear (see schedule, below).
assignments: Asynchronous. Each part of each assignment will be made available to you- on Canvas- at the beginning of the week indicated on the schedule, below. Using either spss or R, you will undertake each assignment on your own and in accordance with your own schedule, and submit to Canvas, on the due date.
workouts: Asynchronous. On weeks on which there is a workout, it will be made available to you- on Canvas- at the beginning of the week (see schedule, below). Workouts constitute optional (but highly recommended) work undertaken on your own and in accordance with your own schedule. They are not submitted. An answer key will be made available to you on Canvas.
office hours: Synchronous. Synchronous office hours will be held in accordance with the schedule, below. When the time comes, you will receive a link.
Canvas discussions: Asynchronous. When the time comes, this feature of Canvas will be activated, and you will be notified.

Note: I have done my best to anticipate the implications of alterations to the course structure, not to mention the simple reality of university life, in response to Covid. However, I have never taught a virtual, largely asynchronous, course in statistics. I would ask for your patience, and also, that, in the event that you encounter shortcomings, you let me know, and work with me to overcome the problems. We all want for the necessary mode of teaching to “work.” We are, however, sailing into uncharted waters.

Note: All asynchronous components of the course will be contained within modules, organized by week, and hosted on the Canvas platform.

Materials

REQUIRED READING:

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.

On weeks on which there are readings, these readings will be made available to you in pdf form- on Canvas- at the beginning of the week. 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.

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:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

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 FALL 2020

Teaching at SFU in fall 2020 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).