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**

The Course Syllabus......

Instructor

Jeremy Jackson

| January 6, 2017

Location:

NW 2690A

| New Westminster

Jordan Peterson: Don't let people inside your head, they may not know what they are doing.

Instructor Contact Information

Email: metrixconsulting@shaw.ca or jacksonj@douglascollege.ca.

Email Availability: I will be available between Monday and Thursday (9 am to 5 pm) for questions, email, etc. If you have questions, please plan to ask them around these times.

Office hours: Tuesday 4:30 pm- 6:30 pm or by appointment on Thursday 4:30 pm - 6:30 pm.

Office number: NW 3431.

Classroom: NW 3412, 2:30-4:20 Tuesday and Thursday

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.

Course Description

The purpose of this course is to teach students with basic knowledge of statistics to analyze data using two popular statistical software packages. Students will gain sufficient familiarity with XLSTAT 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 hypothesis testing and psychological measurement that are not usually addressed in undergraduate statistics courses.

How Does The Course Work

In the course there will be **2 exams** **worth 20% of the course grade each**. Students will have 2 hours IN CLASS to complete each exam. Both exams will consist of essay and multiple choice questions.

There are 12 essay questions for the course. Please see the "learning objectives" document for the 12 questions. I shall randomly select 2 of the questions for each exam. It is highly recommended that you prepare your answers to these questions in advance. I am expecting 2 page, well-written, grammatically correct, thoughtful, and factually correct answers to these questions. Students can bring in to the exam 1 8.5 x 11 sheet of paper with whatever they like written on the paper.

All exams are to be completed in class. **ONLY MEDICAL** extensions are accepted for quizzes. Supporting medical documentation must be provided for a missed exam.

**Students are also required to complete 1 term assignment.** The term assignment is a presentation of an analysis to the class. For 2300 students, each group of 2 students must design, develop, administer, analyze, and present the results of a survey. The survey will be administered to a **minimum of 50** respondents. The survey can be of any type and administered to any set of subjects in which the group is interested (students, faculty, work colleagues, etc). The presentation is 20 minutes long with an additional 10 minutes for questions. The assignment is worth **20% of the final course grade.**

Honors students will present an analysis of their own data. The presentation is 20 minutes with 10 minutes for questions.

There are **4 analysis assignments** in the course. Click on the "Assigments" tab above for details on each of the assignments. Assignments are worth 10% each. Due dates are given in the syllabus.

Week 1
- Jan 5th

Introduction to the course. Survey of basic statistical concepts. Analysis of survey results. Answers to survey questions.

Lecture 1: Summary

Reading: None

Week 2
- Jan 10th & 12th

Intro to SPSS and XLSTAT. Review of research design and statistical basics. Introduction to statistics review: hypothesis testing, estimation, confidence intervals, descriptive statistics. Assignment 1.

Lecture 2: Summary

Reading: None

Week 3
- Jan 17th & 19th

Basics of data management. Types of data files, data types, data entry, auditing, data security, data preparation, data coding, data recoding, data formats, computation of new values.

Missing values introduction (called imputation). Deductive, mean value, regression, hot deck, nearest neighbor.

Lecture 3: Summary

Week 4
- Jan 24th & 26th

Assignment 1 debrief. Missing values ontinued. Basic concepts in psychological measurement.

Assignment 1 dueLecture 4: Summary

Week 5
- Jan 31st & Feb 2nd

Basic concepts in psychological measurement continued. Costruct and criterion validity. Reliability. Using SPSS to assess validity and reliability.

Isolation, and basic ideas in research design and random assignment of subjects to conditions.

Lecture 5: Summary

Week 6
- Feb 7th & Feb 9th

Feb 7th, exam 1 review

Week 8
- Feb 21st & Feb 23rd

First Exam, Feb 21st - 30 multiple choice, 2 SA.

Basic data reduction. Principal components analysis, use of PCA in nearest neighbor missing values method. PCA in XLSTAT.

Lecture 6: Summary

Assignment 2 due Feb 23rd

Week 9
- Feb 28th & Mar 2nd

The DV. Constructing and evaluating scales of measurement. Data reduction vs factor analysis. Calculating reliability, homogeneity and dimensionality in XLSTAT.

Multiple regression. Use of multiple regression in imputation.

Lecture 7: Summary

Week10
- Mar 7th & Mar 9th

Hypothesis testing. XLSTAT and SPSS for dependent an independent groups t-tests. SPSS for one and two-way ANOVA. SPSS for repeated measures ANOVA.

Lecture 8: Summary

Assignment 3 due

Week 12
- Mar 21st & Mar 23rd

Second Exam - 30 multiple choice, 2 SA.

Mar 21st, exam 2 review

Week 13
- Mar 28th & Mar 30th

Presentations

Week 14
- April 4th & April 6th

Presentations

Week 15
- April 11th

Presentations.

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.

Plagiarismoccurs 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.