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Dr Jackson Home 
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Welcome to Applied Research Methods in Psychology. From this page you can access all the information you will need to complete the course. Links are available to course lecture templates, selected lecture notes, readings, learning objectives, and instructor contact information. I hope you enjoy the course. Jeremy Jackson
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The Course Syllabus......
Jeremy Jackson
|    Jan 4, 2024
|     New Westminster
Thomas Edison: "Hell, there are no rules here - we're trying to accomplish something"

Instructor Contact Information

Email: Use the "Mail" function in the main menu on Blackboard.

Email Availability: Please ask substantive questions on Blackboard. Email me for emergencies or issues that can not be adressed on the discussion board in Blackboard.

Office hours: Wednesday, 11:00 am to 1:00 pm Online on Zoom. My Zoom meeting room is here.

Office number: Blackboard, online.

Classroom: NWS-S1802 (12:30-2:20pm)

Email Requirements : All emails should include: 1) Your name, student number and the number of the course you are enrolled in, 2) A salutation such as "Hello Dr Jackson....", 3) An appropriate ending to the email thanking the person for their time in considering your request. For emails about grades, consult this.


Course Description

The purpose of this course is to teach students with basic knowledge of reserach design, data analysis, statistics and measurement to analyze data using two popular software packages - Excel and SPSS. Students will gain sufficient familiarity with Excel and SPSS to conduct univariate, bivariate and multivariate data analyses, estimate population parameters, fit basic linear models and conduct hypotheses tests on experimental data. Many forms of data management including data entry, auditing, imputation, coding, recoding, and transformation will also be covered. By the end of the course, students should be able to conduct an analysis of data generated in a survey or experiment and give a presentation of the results of the analysis.

In addition to covering practical issues faced in the analysis of data, the course also covers basic issues in science, the application of science to real-world problems, qualitative data analysis, hypothesis testing and psychological measurement.


How Does The Course Work

In the course there will be 1 midterm exam worth 20% of the course grade and 1 final exam worth 25% of the course grade. Students will have 70 minutes ON BLACKBOARD, during class time to complete each exam. The exams will consist of multiple choice questions.

All exams are to be completed Online. ONLY MEDICAL conditions are accepted for exam accomodations. Ongoing psychological states and conditions are not medical conditions. To seek accomodations for these kinds of conditions, please see student services. Supporting medical documentation must be provided for a missed exam within 4 days of the exam. There are no exceptions or make-up assignments.

There are 5 analysis exercises/assignments  for marks in the course. Pecentages for each assignment/exercise are given in the syllabus below.

Exercises require the student to do an analysis and then report their results and engage in discussion with other students on the exercises discussion forum on Blackboard. Find the discussion board in the "main menu" in our course on Blackboard.

Assignments require students to complete an analysis of data. Assignments 1-3 are not for marks but will be eligible for tests and class discussion. Assignment 4 is for marks. Use the "Assignments" item in the main menu in our course on Blackboard to hand in your assignment.

There are also two videos to watch called "The Rules" and "How The Course Works". There is a 15 question multiple choice quiz on these videos. A 2.5% bonus mark will be given for completing this test with 100% correct.

Week 1 - Jan 4th

Introduction to the course. Description of course software/materials for the course. Introduction to the course objectives and subject matter.

Watch these videos: How The Course Works, The Rules.

The "How the Course Works" and "The Rules"quiz. Complete on Blackboard before the end of week 2 of the course. 2.5% bonus for quiz.

Week 2 - Jan 11th

Lectures: Lecture 1

Powerpoint: Powerpoint lecture 1

Exercise: Exercise 1, Updated Exercise 1 Data Download and Restructuring Procedure Video

Exercise 1 due between Tuesday Jan 16 and Friday Jan 19th . Complete on the "Exercises" discussion board on Blackboard. 7.5% of course grade.

Week 3 - Jan 18th - ONLINE

Research methods, where do they come from, Feynman, why is science respected, pseudo-science, utter honesty, freedom of expression, the simple experiment, isolation, random assignment

Lectures: Lecture 2: Part 1, Lecture 2: Part 2

Powerpoint: Powerpoint lecture 2

Exercise: Assignment 1

Assignment 1 is a homework assignment. Be prepared to discuss in class.

Week 4 - Jan 25th

Research design, quasi-experiments, in comparison to what, generalizability, meaning

Lectures: Lecture 3: Part 1, Lecture 3: Part 2

Powerpoint: Powerpoint lecture 3

Exercise: Exercise 2, Data File: Annual_data

Exercise 2 due between Tuesday Jan 30th and Friday Feb 2nd. Complete on the "Exercises" discussion board on Blackboard. 7.5% of the course grade.

Week 5- Feb 1st - ONLINE

Univariate and bivariate data analysis

Lectures: Lecture 4, Data Quality

Powerpoint: Powerpoint lecture 4

Assignment - Analysis of change over time in social, economic and climate factors: Assignment 2, Data File: Annual_data

Assignment 2 is a homework assignment. Be prepared to discuss in class.

Week 6 - Feb 8th

Hypothesis testing and estimation.

Lectures: Lecture 5: Part 1, Lecture 5: Part 2, Confidence intervals in spss, Sampling Methods

Powerpoint: Powerpoint lecture 5

Assignment - Error rate by effect size and sample size: Assignment 3

Assignment 3 is a homework assignment. Be prepared to discuss in class.

Week 7 - Feb 15th - ONLINE

Basic concepts in distance, simple regression and multiple regression.

Lectures: Lecture 6, Reflections on Models and Model Error

Powerpoint: Powerpoint lecture 6

Exercise: Exercise 3, Spss Gini Data, Excel Gini Data

Exercise 3 due between Tuesday Feb 27th and Friday Mar 1st. Complete on the "Exercises" discussion board on Blackboard. 7.5% of the course grade.

First Exam - 40 multiple choice. To be written online Thursday Feb 15th between 12:30 pm and 2:30 pm. Online lectures 1-5. In person lectures, and assignments 1, 2 and 3. There is 60 minutes to write and there is no backtracking.

Week 8 - Feb 22nd
Spring Break - No class
Week 9 - Feb 29th

Distance again and Principal components analysis.

Lectures: Lecture 7

Powerpoint: Powerpoint lecture 7, Lecture 7 videos

Exercise: Exercise 4

Exercise 4 due between Tuesday Mar 5th and Friday Mar 8th. Complete on the "Exercises" discussion board on Blackboard. 7.5% of the course grade.

Week 10 - Mar 7th - ONLINE

Basic concepts in measurement.

Lectures: Lecture 8: part 1, Lecture 8: part 2, Measurement in SPSS

Powerpoint: Lecture 8

Exercise/Assignment: None

Week 11- Mar 14th

Hypothesis testing in SPSS for within and betwen subjects cases with 1 IV and 1 DV (One-Way ANOVA). Planned comparisons (the only kind there should be). SPSS for within and between subjects two-way ANOVA.

Lectures: Lecture 9

Powerpoint: N/A

Exercise/Assignment: None

Week 12 - Mar 21st - ONLINE

Second/Final Exam - 40 multiple choice. To be written on Thursday, Mar 21st between 12:30 pm and 2:30 pm.

Week 13- Mar 28th

Lectures: How To Analyze a Data File: Part 1, How To Analyze a Data File: Part 2, How to Analyze a Data File: Part 3, How to Analyze a Data File: Part 4


Week 14 - April 4th

Assignment 4 due Friday, April 12th. Hand in on the "Assignments" menu item in the main menu on Blackboard. 25% of the course grade.

Additional Resources: Not Assigned

The following links are to additional videos that may be refferenced throughout the semester. They are not testable, but they are all valuable, interesting and provide significant insight in to science, the scientific process and the application of science to the real-world.

Politics and science

Predicting the Future

Science and Governments

Cherry Picking

Public Health Messages

Because vs With


Science and Humility


What is a Planet: Operationism and Ordinary Language

Academic Dishonesty - Plagiarism & Cheating

Cheating , which includes plagiarism, occurs where a student or group of students uses or attempts to use unauthorized aids, assistance, materials or methods. Cheating is a serious educational offense.

Plagiarism occurs where the student represents the work of another person as his or her own. Douglas College condemns all forms of cheating.

The college will discipline students found to be cheating. Discipline may include:

1. a grade of zero may be awarded for the affected assignment, test, paper, analysis, etc.;

2. a failing grade may be assigned in the affected course;

3. referral to the College President for the assignment of discipline, which may include suspension from the college.

Test Policy

All tests are to be completed ONLINE. ONLY MEDICAL extensions given prior to the assessment are accepted for quizzes, exercises and assignments. Supporting medical documentation must be provided for a missed quiz within 4 days of the test. Ongoing psychological states and conditions are not medical. To seek accomodations for these conditions consult student services. Threre are NO MAKEUP ASSIGNMENTS IN THE COURSE.

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