Psychology 2812B 001 FW25
Statistics for Psychology II
Western University
London Canada
Department of Psychology
Fall/Winter 2025
Psychology 2812B Section 001
Statistics for Psychology II
1 Calendar Description
In this course, students learn advanced data analytic techniques for psychological research. Topics include advanced analyses within the general linear model (GLM), e.g., multiple and logistic regression, as well as special applications of the GLM such as ANOVA. Students continue to gain experience in computer-based analytic methods and coding techniques.
Antirequisite(s): the former Psychology 2810; the former Psychology 2820E.
Prerequisite(s): At least 70% in Psychology 2811A/B; at least 60% in Data Science 1000A/B and at least 60% in 0.5 credit of Year 1 Math from among the following courses: Calculus 1000A/B, Calculus 1301A/B, Calculus 1500A/B, Calculus 1501A/B, Mathematics 1225A/B, Mathematics 1228A/B, Mathematics 1229A/B, Mathematics 1600A/B, or Applied Mathematics 1201A/B, or registration in Year 2 of an Honours Specialization in Neuroscience with special permission from the program administrator. Math 1228A/B is recommended. Students who have completed Statistics 1024A/B (or other Year 1 introductory statistics course in addition to 0.5 credit of Year 1 Math) instead of Data Science 1000A/B may enrol after completing an introductory programming class from the following list: Computer Science 1025A/B, Computer Science 1026A/B, Computer Science 2120A/B, Data Science 1200A/B, Digital Humanities 2220A/B, or Engineering Science 1036A/B. Data Science 2000A/B may be substituted for Data Science 1000A/B for students entering the program with 1.0 credits of Year 1 Math courses.
2 lecture hours and 2 laboratory hours, 0.5 course
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: Paul F. Tremblay, PhD
Office: see Brightspace for location
Office Hours: Mondays 1-3 pm
Email: ptrembla@uwo.ca
Teaching Assistants: Contact info for all TAs and lab sections will be posted to Brightspace
Time and Location of Classes: see Timetable on Student Centre
3 Course Materials
There is no specific textbook for this course. Readings will be drawn from online textbooks, tutorial journal articles, available freely in pdf format online. The links will be available in the course reading list in Brightspace.
4 Course Objectives and Learning Outcomes
This course focuses on statistical procedures used to analyze data collected through specific research designs and measurement strategies. Emphasis is placed on describing sample data, drawing inferences about populations, and evaluating effect sizes and the precision of estimates. In psychology, hypotheses often concern the relationships between variables, where some serve as explanations (predictors or IVs) for others (outcomes or DVs). Many of the methods covered fall under the general linear model, which frames the outcome (dependent variable) as a linear function of one or more explanatory (independent) variables.
The overall objectives of the course are to develop:
1. A solid understanding of foundational statistical concepts such as effect size, sources of variation, statistical control, and standard error;
2. Proficiency in selecting appropriate statistical techniques and implementing them using statistical software (with a focus on R); and
3. The ability to accurately interpret and clearly report the results of data analyses.
|
Learning Outcome |
Learning Activity |
Assessment |
|
Depth and Breadth of Knowledge
|
Lectures, readings and lab activities and assignments
|
Research assignments, exams |
|
Knowledge of Methodologies
|
Lectures, readings and lab activities and assignments
|
Research assignments, exams
|
|
Application of Knowledge
|
Lectures, readings and lab activities and assignments
|
Research assignments, exams
|
|
Communication Skills
|
Lectures, readings and lab activities and assignments:
The lab assignments require students to generate ideas and polish their ability to interpret and report results clearly in standard style (e.g., APA), tables and figures. |
Research assignments, exams |
|
Awareness of Limits of Knowledge
|
Lectures, readings and lab activities and assignments:
Labs and reports immerse students in real world challenging data to illustrate limitations more clearly |
Research assignments, exams
|
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Autonomy and Professional Capacity
|
Lectures, readings and lab activities and assignments
Lectures and labs integrate real world examples of challenges in research methodology that require sound judgement.
Lectures encourage students to develop their skills in various applied and professional domains including evaluation and policy research, randomized controlled trials in health research, and academic research. |
Research assignments, exams
|
5 Evaluation
Midterm test 20%
Final Exam 30%
Five Lab Assignments 50%
The evaluation and testing formats for this course were created to assess the learning objectives as listed in section 4 and are necessary for meeting these learning objectives
Midterm Test and Final Exam: Both the midterm test and final exam will consist of multiple-choice, and short answer questions. No aids will be allowed as these evaluations will focus on your understanding of statistical concepts and procedures and your ability to interpret results. A specific breakdown of the type and number of questions will be confirmed prior to the test/exam. The final exam is cumulative, with emphasis placed on content from the second half of the course.
Five Lab Assignments: Each assignment will focus on a different aspect of the lab sessions and will be worth 10% of your final grade. The lab assignments will consist of working with data sets, writing short script in R to conduct the necessary statistical analyses, interpreting the statistical analyses, reporting key results in APA format, and answering specific questions related to the interpretation and consequences of results. Each lab report must be submitted to Gradebook by 11:59 pm on the respective due date.
Policy on Missing Coursework
Midterm test is the Designated Assessment. If you miss the midterm, you will need to seek formal supporting documentation. A makeup test will be granted if approved by academic counselling. Dates for midterm make-up test will be announced via Brightspace. It is the student’s responsibility to check this date and ensure that they are available to write on the specified day if a make-up exam is required. The makeup may adhere to a different format from the original test.
Final Exam. The final exam is scheduled by the Office of the Registrar and requires formal supporting documentation. Students who receive academic consideration for an exam will be given an opportunity to write a makeup exam. The makeup may adhere to a different format from the original exam.
Five Lab Assignments. Students need to complete all five assignments, and all five assignments will be equally weighted in the calculation of your overall grade. In terms of the course flexibility in assessment component, you will be allowed a 48-hour extension on one of the first four assignments. (The schedule for the 5th assignment already includes an extra week for completion.) Any additional extension may be granted with academic consideration. In the interest of fairness to the teaching assistants, extensions cannot be granted for more than two weeks past the original deadline.
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
Midterm: (Feb 25, in class) 20%
Final Exam: (as scheduled by registrar during final exam period) 30%
Lab Assignments: (Five Assignments each weighted 10%) 50%
Assignment 1: Assigned Jan 14; Due Jan 28
Assignment 2: Assigned Jan 28; Due Feb 11
Assignment 3: Assigned Feb 11; Due Mar 4
Assignment 4: Assigned Mar 4; Due Mar 18
Assignment 5: Assigned Mar 18; Due Apr 8
Lab assignments will be assigned during lab sessions, and you must submit them to Brightspace by 11:59pm on the date indicated above.
7 Class and Lab Schedule
See Brightspace Content Pages for weekly suggested readings.
|
Lec |
Lecture Topic |
Lab |
|
Jan 7 |
Overview and introduction to R and RStudio |
More in-depth demo of RStudio (and other packages such as jamovi and Jasp) |
|
Jan 14 |
Working with data |
Assign 1 (due Jan 28). Data visualization and descriptive statistics |
|
Jan 21 |
Inferential statistic, effect size and power (t-test) |
Data inspection: distribution properties and extreme/outlier cases |
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Jan 28 |
ANOVA and contrasts |
Assign 2 (due Feb 11). Statistical tests, effect size, confidence intervals, and power |
|
Feb 4 |
Factorial ANOVA and interactions |
Statistical power and sample size calculation software |
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Feb 11 |
Repeated Measures ANOVA |
Assign 3 (due Mar 4). Data set up and analysis for a simulated RCT in ANOVA |
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Feb 18 |
READING WEEK |
No lab |
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Feb 25 |
MIDTERM (in-class) |
No lab |
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Mar 4 |
Bivariate and multiple correlation |
Assign 4 (due Mar 18). Correlational analysis with statistical control |
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Mar 11 |
Bivariate linear regression and general linear model (GLM) |
Understanding statistical control in partial correlations and subgroup analysis |
|
Mar 18 |
Multiple linear regression |
Assign 5 (due Apr 8). Analysis of data set with multiple regression and GLM |
|
Mar 25 |
GLM and ANCOVA |
Categorical predictors and moderation in multiple linear regression |
|
Apr 1 |
Logistic regression |
Multiple regression diagnostics and recommended table format |
|
Apr 8 |
Factor analysis |
Review for exam |
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.
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.
AI Policy for Psychology 2812B:
Responsible use of AI is allowed in 2812B. This includes using AI for brainstorming, improving grammar, or doing preliminary/background research on a topic.
AI is not to be used in place of critical thinking.
The misuse of AI undermines the academic values of this course. Relying on AI to create full drafts or fabricate sources is prohibited. You are ultimately responsible for any work submitted, so it is highly advised that you critically review your Generative AI output before incorporating this information into your assignments.
If you use AI, you must clearly explain its role in your work. All written assignments will require an AI Usage Statement, in which you will indicate what tools you have used, what you have used them for, and (broadly) how you have modified this information. Assignments without an AI Usage Statement will not be accepted.
Violations of this policy will be handled according to Western’s scholastic offense policies.
Multiple Choice Exams
Computer-marked multiple-choice tests and/or exams will be subject to submission for similarity review by software that will check for unusual coincidences in answer patterns that may indicate cheating.
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.
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
Academic Considerations: https://registrar.uwo.ca/academics/academic_considerations/index.html
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.
