Psychology 3801F 001 FW24
Statistics for Psychology III
Western University
London Canada
Department of Psychology
Fall 2024
Psychology 3801F Section 001
Statistics for Psychology III
1 Calendar Description
This course extends beyond traditional single-sample datasets. Students work with data on a larger scale by examining population data and implementing basic meta-analyses using a modern coding language. In addition, students extend their knowledge of statistical decision-making by learning to apply basic Bayesian models of statistical decision-making. Antirequisite(s): the former Psychology 3800F/G. Extra Information: 2 lecture hours and 2 laboratory hours.
Antirequisites are courses that overlap sufficiently in content that only one can be taken for credit. If you take a course that is an antirequisite to a course previously taken, you will lose credit for the earlier course, regardless of the grade achieved in the most recent course.
RESTRICTED TO MAIN CAMPUS HONS SPECIALIZATION IN PSYCH, DEVELOPMENTAL COGNITIVE NEUROSCIENCE, AND ANIMAL BEHAVIOUR.
WAIT LIST OPTION AVAILABLE.
REQUISITES: Prerequisite(s): At least 75% in Psychology 2802F/G and Psychology 2812A/B, plus registration in third or fourth year Honours Specialization in Psychology or Honours Specialization in Developmental Cognitive Neuroscience, or Honours Specialization in Animal Behaviour.
Course Weight: 0.5
Unless you have either the prerequisites for this course or written special permission from your Dean to enrol in it, you may be removed from this course and it will be deleted from your record. This decision may not be appealed. You will receive no adjustment to your fees in the event that you are dropped from a course for failing to have the necessary prerequisites.
2 Course Information
Instructor: J Bruce Morton
Office: see Brightspace
Office Hours: By appointment
Email: bmorton3@uwo.ca
Teaching Assistant: Niki Sinha
Office: see Brightspace
Office Hours: By appointment
Email: nsinha7@uwo.ca
Time and Location of Classes: See Student Centre Timetable
3 Course Materials
Lecture slides for PSY3801 are available in the Resources folder of the OWL Brightspace website for the course.
Required readings for PSY3801 are available in the Resources folder of the OWL Brightspace website for the course.
Software for PSY3801 is R. Required packages are available on the internet for free and can be installed within R-studio.
Assignments will be posted and submitted on Brightspace.
Quizzes will be posted and submitted on Brightspace.
4 Course Objectives and Learning Outcomes
The primary goal of PSY3801 is to provide students with logical and statistical skills required to critically evaluate data and research literature. It will achieve this goal by providing students with an in-depth introduction to two advanced statistical procedures: Bayesian analysis and meta-analysis. Through lectures, tutorials, readings, and homework assignments, students will learn the underlying rationale for both procedures, work with sample data sets in R to acquire a basic mastery of core techniques, learn basic diagnostic procedures, and learn to report the results of their analyses in written text and basic tables. Upon completing the course, students will: understand the difference between null hypothesis significance testing (NHST) and Bayesian inference; be capable of critically evaluating research literature by identifying uncertainties surrounding prevailing psychological theories and detecting biases in the reporting of evidence; and be capable of interpreting and producing written reports of Bayesian and meta-analytical statistical analyses. These skills will help students recognize the limits of scientific knowledge.
After successfully completing this course, students should be able to:
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Learning Outcome |
Learning Activity |
Assessment |
|
Depth and Breadth of Knowledge.
|
Lectures
Readings
|
Assignments
Quizzes
Exams |
|
Knowledge of Methodologies.
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Lectures Readings Coding and analysis assignments |
Assignments
Quizzes
Exams |
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Application of Knowledge.
|
Coding and analysis assignments |
Assignments
Quizzes
Exams |
|
Communication Skills.
|
Readings Coding and analysis assignments |
Assignments
Quizzes
Exams |
|
Awareness of Limits of Knowledge.
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Lectures Readings
|
Assignments
Quizzes
Exams |
|
Autonomy and Professional Capacity.
|
Lectures |
|
5 Evaluation & Policy on Missing Coursework
The evaluation and testing formats for this course were created to assess the learning objectives as listed in section 4.0 and are considered necessary for meeting these learning objectives. The evaluation components of the course consist of the following:
Assignments: 4 x 1.25 = 5% of final mark
Quizzes: 3 x 10 = 30% of final mark
Midterm = 32.5% of final mark
Final exam = 32.5% of final mark
Assignments help students learn lecture materials through practicing sample problems. Therefore, due dates for and grading of the Assignments are flexible. Students have 9 days to complete each Assignment but can take up to an additional week to submit their work. As well, students receive 1.25 marks for each submitted assignment regardless of the correctness of their work. Please note that because the submission deadline for Assignments already includes flexibility in the form of a 1-week grace period, the instructor reserves the right to deny academic consideration for assignments which are submitted following the end of the period of flexibility. Late Assignments without academic consideration following the period designated above will be subject to a late penalty of 5%/day.
Quizzes are designed to help students track their mastery of concepts and procedures and to familiarize them with the testing procedures used in the course. Because workload demands can vary through the term, students are not expected to write or be fully prepared for all 4 quizzes. Therefore, the final quiz mark will be based on the top 3 of the 4 quiz marks. Please note, because not all elements of this assessment (i.e., the final Quiz mark is based on the top 3 of 4 administered quizzes) are required in the calculation of the final course grade, the instructor reserves the right to deny academic consideration for these missed elements.
The Midterm will consist of SA questions based on readings and lectures pertaining to Bayesian statistics. Students will be allowed to use R and scripts that have been distributed in class. R-scripts CANNOT be annotated with additional notes or course materials. Laptop computers cannot be connected to the internet during the exam. Please note that this assessment is central to the learning objectives for this course. Accordingly, students seeking academic consideration for this assessment will be required to provide formal supporting documentation. Students who are granted academic consideration for this assessment will be provided one opportunity write a make-up exam no more than 1 week following the scheduled Midterm exam.
The Final exam will consist of SA questions based on readings and lectures pertaining to meta-analysis. Students will be allowed to use R and scripts that have been distributed in class. R-scripts CANNOT be annotated with additional notes or course materials. Laptop computers cannot be connected to the internet during the exam. Please note that this assessment will be scheduled by the Office of the Registrar and that supporting documentation is always required for academic consideration requests for examinations scheduled by the office of the registrar. Students who are granted academic consideration for this assessment will be provided one opportunity write a make-up exam no more than 1 week following the scheduled Final exam.
This course is exempt from the Senate requirement that students receive assessment of their work accounting for at least 15% of their final grade at least three full days before the date of the deadline for withdrawal from a course without academic penalty.
The Psychology Department follows Western’s grading guidelines: https://www.uwo.ca/univsec/pdf/academic_policies/general/grades_undergrad.pdf
The expectation for course grades within the Psychology Department is that they will be distributed around the following averages:
70% 1000-level to 2099-level courses
72% 2100-2999-level courses
75% 3000-level courses
80% 4000-level courses
In the event that course grades are significantly higher or lower than these averages, instructors may be required to make adjustments to course grades. Such adjustment might include the normalization of one or more course components and/or the re-weighting of various course components.
Policy on Grade Rounding
Please note that although course grades within the Psychology Department are rounded to the nearest whole number, no further grade rounding will be done. No additional assignments will be offered to enhance a final grade; nor will requests to change a grade because it is needed for a future program be considered.
6 Assessment/Evaluation Schedule
Assignment due dates: September 27; October 11; November 15; November 29
Quizzes: In tutorials September 26/27; October 10/11; November 14/15; November 28/29
MIDTERM exam: In class on October 30
FINAL: to be scheduled by the Registrar’s Office
7 Class Schedule
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LECTURE #/DATE |
TOPIC |
QUIZZES/ASSIGNMENTS |
READINGS |
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L1: Week of Sept 11 |
Introduction |
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|
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L2: Week of Sept 18 |
Introduction to Bayes |
ASSIGNMENT 1 assigned |
Navarro, D. J. (2018). Learning statistics with R: A tutorial for psychology students and other beginners. Ch 17.5
McClave & Sincich, Ch 3.5 |
|
L3: Week of Sept 25 |
Bayes Theorem |
ASSIGNMENT 1 due Sept 27
QUIZ 1 (during tutorial) |
McClave & Sincich, Ch 4.2, 4.4, Ch5 (optional)
Coghlan, A. (2017) “A little book of R…” |
|
L4: Week of Oct 2 |
Bayesian estimation |
ASSIGNMENT 2 assigned |
Meredith & Kruschke (2021). Bayesian analysis supersedes the t-test.
Kruschke (2013). Bayesian estimation supersedes the t-test. JEP. |
|
L5: Week of Oct 9 |
Bayesian model comparison I |
ASSIGNMENT 2 due Oct 11
QUIZ 2 (during tutorial) |
Navarro, D. J. (2018). Learning statistics with R: A tutorial for psychology students and other beginners. Ch 17.2; 17.7
|
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Week of Oct 16 |
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READING WEEK |
|
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L6: Week of Oct 23 |
Bayesian model comparison II |
|
Navarro, D. J. (2018). Learning statistics with R: A tutorial for psychology students and other beginners. Ch 17.8
|
|
Week of Oct 30 |
|
MIDTERM |
|
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L7: Week of Nov 6 |
Meta-analysis: Intro |
ASSIGNMENT 3 assigned |
Lowe et al., (2021). The bilingual advantage in children’s executive functioning is not related to language status. Psych Sci |
|
L8: Week of Nov 13 |
Meta-analysis: modelling effect sizes |
ASSIGNMENT 3 due Nov 15
QUIZ 3 (during tutorial) |
|
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L9: Week of Nov 20 |
Meta-analysis: effect size heterogeneity and moderation analysis |
ASSIGNMENT 4 assigned |
|
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L10: Week of Nov 27 |
Meta-analysis: publication bias |
ASSIGNMENT 4 due Nov 29
QUIZ 4 (during tutorial) |
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Dec 4 |
REVIEW |
|
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8 Academic Integrity
Scholastic offences are taken seriously, and students are directed to read the appropriate policy, specifically, the definition of what constitutes a Scholastic Offence, at the following Web site: https://www.uwo.ca/univsec/pdf/academic_policies/appeals/scholastic_discipline_undergrad.pdf.
Possible penalties for a scholastic offence include failure of the assignment/exam, failure of the course, suspension from the University, and expulsion from the University.
Statement on Use of Electronic Devices
For both the Midterm and Final exams, students will be allowed to use R and scripts that have been distributed in class. R-scripts CANNOT be annotated with additional notes or course materials. Laptop computers cannot be connected to the internet during any exam.
Plagiarism Detection Software
All required papers may be subject to submission for textual similarity review to the commercial plagiarism detection software under license to the University for the detection of plagiarism. All papers submitted for such checking will be included as source documents in the reference database for the purpose of detecting plagiarism of papers subsequently submitted to the system. Use of the service is subject to the licensing agreement, currently between Western and Turnitin.com.
Use of AI
The use of generative AI tools such as ChatGPT to produce written work is not permitted unless permission is granted by the instructor for specific circumstances. Any work submitted must be the work of the student in its entirety unless otherwise disclosed. When used, AI tools should be used ethically and responsibly, and students must cite or credit the tools used in line with the expectation to use AI as a tool to learn, not to produce content.
Exam Proctoring Software
Tests and examinations for online courses may be conducted using a remote proctoring service. More information about this remote proctoring service, including technical requirements, is available on Western’s Remote
Proctoring website at: https://remoteproctoring.uwo.ca.
Personal Response Systems (“Clickers”)
In classes that involve the use of a personal response system, data collected will only be used in a manner consistent to that described in this outline. It is the instructor’s responsibility to make every effort to ensure that data remain confidential. However, students should be aware that as with all forms of electronic communication, privacy is not guaranteed.
9 Academic Accommodations and Accessible Education
View Western’s policy on academic accommodations for student with disabilities at this link.
Accessible Education provides supports and services to students with disabilities at Western.
If you think you may qualify for ongoing accommodation that will be recognized in all your courses, visit Accessible Education for more information. Email: aew@uwo.ca Phone: 519 661-2147
10 Absence & Academic Consideration
View Western’s policy on academic consideration for medical illnesses this link
Find your academic counsellor here: https://www.registrar.uwo.ca/faculty_academic_counselling.html
Students must see the Academic Counsellor and submit all required documentation in order to be approved for certain academic considerations. Students must communicate with their instructors no later than 24 hours after the end of the period covered SMC, or immediately upon their return following a documented absence.
Medical Absences
Submit a Student Medical Certificate (SMC) signed by a licensed medical or mental health practitioner to Academic Counselling in your Faculty of registration to be eligible for Academic Consideration.
Nonmedical Absences
Submit appropriate documentation (e.g., obituary, police report, accident report, court order, etc.) to Academic Counselling in your Faculty of registration to be eligible for academic consideration. Students are encouraged to contact their Academic Counselling unit to clarify what documentation is appropriate.
Religious Consideration
Students seeking accommodation for religious purposes are advised to contact Academic Counselling at least three weeks prior to the religious event and as soon as possible after the start of the term.
11 Other Information
- Office of the Registrar: https://registrar.uwo.ca
- Student Development Services: www.sdc.uwo.ca
- Psychology Undergraduate Program: https://www.psychology.uwo.ca/undergraduate/index.html
Students who are in emotional/mental distress should refer to Health and Wellness@Western https://www.uwo.ca/health/ for a complete list of options about how to obtain help.
Please contact the course instructor if you require material in an alternate format or if you require any other arrangements to make this course more accessible to you.
If you wish to appeal a grade, please read the policy documentation at: https://www.uwo.ca/univsec/pdf/academic_policies/appeals/appealsundergrad.pdf. Please first contact the course instructor. If your issue is not resolved, you may make your appeal in writing to the Undergraduate Chair in Psychology (psyugrd@uwo.ca).
Copyright Statement
Lectures and course materials, including power point presentations, outlines, videos and similar materials, are protected by copyright. You may take notes and make copies of course materials for your own educational use. You may not record lectures, reproduce (or allow others to reproduce), post or distribute any course materials publicly and/or for commercial purposes without the instructor’s written consent.
12 Land Acknowledgement
We acknowledge that Western University is located on the traditional territories of the Anishinaabek, Haudenosaunee, Lūnaapéewak, and Chonnonton. Nations, on lands connected with the London Township and Sombra Treaties of 1796 and the Dish with One Spoon Covenant Wampum. This land continues to be home to diverse Indigenous Peoples (First Nations, Métis and Inuit) whom we recognize as contemporary stewards of the land and vital contributors of our society.
