Syllabus 202001 05 PDF

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Version Date: 2020-01-05

Psyc 305: Statistics for Experimental Design Course Information: Psych 305 (3 Credits) Winter 2020 Course Website: https://mycourses2.mcgill.ca Prerequisites: Psych 204 or an equivalent introductory statistics course. Lecture: Tuesday/Thursday, Typical schedule: 2:35pm – 3:30pm Weeks without labs: 2:35pm – 3:55pm Room: McIntyre Medical Building, 522 Computer Lab: One 50 minute session per week Room: 2001 McGill College, Room 466

Instructor Information: Carl F. Falk, PhD Office: 2001 McGill College, Room 753 Email: [email protected] Office Hours: Thursdays 10-11am, or by appointment Phone: 514-398-6133 (office) Email is the best way to contact me. I will try to reply within 24-48 hours. Teaching Assistants: Raymond Luong ([email protected]) Camiel van Zundert ([email protected]) Sally Xie ([email protected]) Sunmee Kim ([email protected]) TEAM Peer Mentors: Ella Sahlas ([email protected]) Rachel Dufour ([email protected]) Stefan Pirvu ([email protected])

Course Description This course is intended as an introduction to statistical methods used for analyzing data from experimental and similar research designs used in the social sciences, focusing

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primarily on analysis of variance (ANOVA) and accompanying post-hoc comparisons. Upon completion of the course, students are expected to be able to choose an appropriate statistical method for data from studies conducted within this framework, conduct appropriate analyses, understand underlying assumptions, and interpret/report results.

Instructional Method The course will mainly consist of lectures, hands-on lab assignments, and midterm/final exams.

Labs: Students are expected to attend two lectures (Tuesday and Thursday) and one computer lab. The computer lab will be conducted in 2001 McGill College, Room 466. During the lab, a teaching assistant will guide students how to conduct analyses using SPSS for Windows for the same statistical methods covered in lecture. Students are to choose ONE of 12 lab sessions from the following:

Thursday

Friday

Monday Tuesday

Lab 1 Lab 2 Lab 3 Lab 4 Lab 5 Lab 6 Lab 7 Lab 8 Lab 9 Lab 10 Lab 11 Lab 12

2001 McGill College, Room 466 Thursday, 4:00pm – 4:50pm Friday, 9:00am – 9:50am Friday, 10:00am – 10:50am Friday, 11:00am – 11:50am Friday, 12:00pm – 12:50pm Friday, 1:00pm – 1:50pm Friday, 2:00pm – 2:50pm Monday, 9:00am – 9:50am Monday, 3:00pm – 3:50pm Monday, 4:00pm – 4:50pm Tuesday, 9:00am – 9:50am Tuesday, 1:00pm – 1:50pm

Note that we have attempted to schedule relevant labs to take place after the relevant Thursday lecture on the syllabus. Example: For Session 2, the last Thursday lecture is on January 16. The relevant labs then take place on Jan 16, 17, 20, and 21. Students are required to select which computer lab they will attend during the semester, and register for the session of their choice on Minerva. The maximum number of students per lab session is 35. Students may not register for a lab session that reaches this maximum capacity. Students may also not move from one lab session to another after registration is complete. The lab sessions will be open during the first week of the course at a designated time listed by the course instructor. Registration will be on a first come first serve basis.

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Resources Required Course Materials: Field, A. (2018). Discovering Statistics Using IBM® SPSS Statistics, North American Edition (Fifth Edition). Thousand Oaks, CA: SAGE Publications, Inc. The book has an accompanying website with additional information per chapter/topic, including self-assessment multiple choice questions: https://edge.sagepub.com/field5e

Other Resources (not required): The following are alternative textbooks that cover similar content to that in the required course materials. Abdi, H., Edelman, B., Valentin, D., & Dowling, W. J. (2009). Experimental Design and Analysis for Psychology. Oxford: Oxford University Press. Ferguson, G. A., & Takane, Y. (1989). Statistical Analysis in Psychology and Education (6 th Edition). New York: McGraw-Hill. Field, A., Miles, J., & Field, Z. (2012). Discovering Statistics Using R. Los Angeles: SAGE Publications. Keppel, G., & Wickens, T. D. (2004). Design and Analysis. A Researcher’s Handbook (4 th Edition). New Jersey: Prentice Hall.

Software: Completion of individual lab assignments (discussed below) requires use of SPSS. Note that in addition to the room where labs are conducted, SPSS is available on all workstations in McGill Library Computer Labs (Excluding Apple/Mac computers): https://www.mcgill.ca/library/services/computers#Software https://www.mcgill.ca/library/services/computers/workstations https://www.mcgill.ca/library/services/computers/computer-finder Information regarding when room 466 or other computer labs in the Psychology Department are available will be distributed during the second week of the course.

Calculator: For the midterm and final exam, you are permitted to use a calculator that can perform basic arithmetic operations. Programmable calculators or calculators that can store text or formulas are not allowed.

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Memorization of Formulae: It is not required that you memorize every formula that appears in the textbook or in lecture materials. It is more important to understand statistical concepts rather than computation, and the majority of tested material will focus on such concepts. However, working with and trying to understand formulas through assignments and application can help your understanding of the course material and statistical concepts. Computations using such formulas may appear on the midterm and final exam. A list of such formulas will be posted to myCourses and provided at the midterm/final exam.

Evaluation/Assignments and Grading In the event of extraordinary circumstances beyond the University’s, Department’s, and/or Instructor’s control, the content and/or evaluation scheme in this course is subject to change.

Individual Assignments (30% of total grade) Working on an individual-basis, students are required to conduct quantitative analysis of various data sets by using SPSS for Windows, and practice some hand computations or other statistical concepts. For all assignments, students are permitted to ask teaching assistants questions during office hours or via discussion boards on myCourses. However, students are not to discuss solutions/answers or what the solutions/answers should be, either with teaching assistants, TEAM peer mentors, or with their fellow students prior to submission. If some students are suspected of not abiding by this requirement, they will be awarded a mark of 0 for that assignment. All assignments are to be done independently. This ensures the integrity of the assignments, and it is most beneficial for each student to try to master the material. It is currently planned that assignments will be completed using the “Quiz” feature of myCourses, and different lab sessions and individual students may be required to complete the same questions, but using different datasets. Assignments will be due before the beginning of the computer lab class on the assignment due date. Students are responsible for ensuring that the assignment was submitted successfully via myCourses. Your instructor reserves the right to change the form of submission to electronic documents (i.e., pdf uploaded to myCourses), or hard-copies of assignments on a class-wide or lab-wide basis. We will not accept any assignments via email. Assignments will be subject to a 20% deduction per day late, and assignments will not be accepted after 4 days. Extensions will not be granted, and teaching assistants or TEAM mentors are not authorized to grant extensions. However, the lowest of assignment grade will be omitted from computation of assignment grades. This means that computation of the

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assignment grade for the course will be done out of 6 assignments, each being worth 5% of the total final grade. The tentative list of specific individual assignments is as follows:       

Assignment #1: Descriptive statistics and t tests Assignment #2: One-way ANOVA Assignment #3: Two-way ANOVA Assignment #4: One-way repeated measures ANOVA Assignment #5: Correlation and simple linear regression Assignment #6: Multiple linear regression Assignment #7: Analysis of covariance

Midterm Exam (25% of total grade). The midterm exam is currently scheduled for February 27. The exact date/time/location will be confirmed later in the semester. The midterm exam is closed-book and will cover material from approximately 1-7 on the list of topics. There will be NO make-up exam for the midterm. Under special circumstances (e.g., illness, family emergency) the final exam will serve as a make-up (proof/documentation may be requested).

Final Exam (45% of total grade) The final exam is closed-book and cumulative. Material from the entire course may appear on the final exam.

Optional Extra Credit (up to 1% of total grade) In order to increase understanding of the science of psychology, you can participate in research conducted by members of the McGill Psychology Department. It is an opportunity for you to learn more directly about how questions are investigated empirically with systematic research. You are welcome to participate in the participant pool or to do the non-participatory alternate assignments for an extra 1% of your final grade. Participating is entirely voluntary and is between you and the Participant Pool Teaching Assistant, who will indicate to me at the end of the semester who participated and for how much credit. You are permitted to participate in any study for which you are eligible. Please see https://www.mcgill.ca/psychology/files/psychology/student_faq.pdf for further information. All questions about the participant pool should be sent to the pool TA at: [email protected]

Other Important Policies and Statements Supplemental The passing grade for this course is a C. A supplemental or deferred exam will be available only for (1) those who obtain a D or F in the course; or (2) those who miss the scheduled final

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exam for an acceptable reason. Application to write a supplemental or deferred exam must be made to the Office of the Associate Dean of Arts/Science in Dawson Hall. The supplemental or deferred exam will be offered in the supplemental exam period in August.

Language of Submission In accord with McGill University’s Charter of Students’ Rights, students in this course have the right to submit in English or in French any written work that is to be graded. This does not apply to courses in which acquiring proficiency in a language is one of the objectives. Conformément à la Charte des droits de l’étudiant de l’Université McGill, chaque étudiant a le droit de soumettre en français ou en anglais tout travail écrit devant être noté (sauf dans le cas des cours dont l’un des objets est la maîtrise d’une langue).

Academic Integrity McGill University values academic integrity. Therefore, all students must understand the meaning and consequences of cheating, plagiarism and other academic offences under the Code of Student Conduct and Disciplinary Procedures (see www.mcgill.ca/students/srr/honest/ for more information). L'université McGill attache une haute importance à l’honnêteté académique. Il incombe par conséquent à tous les étudiants de comprendre ce que l'on entend par tricherie, plagiat et autres infractions académiques, ainsi que les conséquences que peuvent avoir de telles actions, selon le Code de conduite de l'étudiant et des procédures disciplinaires (pour de plus amples renseignements, veuillez consulter le site www.mcgill.ca/students/srr/honest/)

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Tentative List of Topics Disclaimer: The list of topics and schedule is tentative and subject to change. Session

Lecture (McMed 522)

Computer Lab (2001 McGill College, Rm. 466) No Lab

1

Jan 7 Jan 9

Course overview Basic statistics

2

Jan 14 Jan 16

Comparing one/two means

3

Jan 21 Jan 23

One-way ANOVA I

4

Jan 28 Jan 30

One-way ANOVA II

5

Feb 4 Feb 6

Two-way ANOVA I

6

Feb 11 Feb 13

Two-way ANOVA II

7

Feb 18 Feb 20

Repeated measures ANOVA

8

Feb 25 Feb 27

Midterm Exam: Feb 27

9

Mar 3 Mar 5

10

Mar 10 Mar 12

Correlation and simple linear regression

11

Mar 17 Mar 19

Multiple linear regression

12

Mar 24 Mar 26

Analysis of covariance

13

Mar 31 Apr 2

Mixed models

No Lab

14

Apr 7 Apr 9

“Robust” statistics

No Lab

Jan 16, 17, 20, 21 Jan 23, 24, 27, 28 Jan 30, 31, Feb 3, 4

Basic SPSS exercise, descriptive statistics, z & t tests

Feb 6, 7, 12, 13

Two-way ANOVA: Basic analyses

Feb 13, 14, 17, 18 Feb 18, 19, 24, 25

One-way ANOVA: Basic analyses

Assignment Due

Assignment #1

One-way ANOVA: Advanced analyses Assignment #2

Two-way ANOVA: Advanced analyses One-way repeated measures ANOVA

Assignment #3

No Lab Study Break Mar 12, 13, 16, 17 Mar 19, 20, 23, 24 Mar 26, 27, 30, 31

Correlation & simple linear regression

Assignment #4

Multiple linear regression

Assignment #5

Analysis of covariance

Assignment #6 Assignment #7...