Fall 2018 - PSYC 301 D100

Intermediate Research Methods and Data Analysis (4)

Class Number: 2899

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 4 – Dec 3, 2018: Mon, 2:30–4:20 p.m.
    Burnaby

  • Exam Times + Location:

    Dec 12, 2018
    Wed, 8:30–11:30 a.m.
    Burnaby

  • Prerequisites:

    PSYC 201 and 210 and a minimum CGPA of 2.67.

Description

CALENDAR DESCRIPTION:

A continuation of PSYC 201 and 210. Provides extensions of the basic theory and methods of research design and data analysis. Includes discussions of the analysis of substantive problems, the choice of appropriate research designs, and special problems that arise in the analysis of psychological data. Quantitative.

COURSE DETAILS:

1. This course is about statistics, data analysis and related matters. Why do we spend time on this material? Because

High quality empirical research in the social sciences is possible only through a thorough understanding of statistics/data analysis.

Statistics is difficult.

Most of the difficulty arises as a result of a dense terminology, and the need for precise, logical thought.

2. Aim of Course:

To develop a competency in thinking about certain statistical issues as they arise in psychology/An understanding of what you, and others, are doing when doing statistics.

Note: A deep understanding of mathematics is not required. The ability to think logically is required.

Note: You will not walk out of this course a master data analyst. Mastery takes years.

If you do well in Psyc301, you should take Psyc410 (advanced ANOVA) and Psyc411 (multivariate analysis). Make no mistake: Honours theses involve complicated analyses and if you are planning to do an honours, you will thank yourself for taking the time to gain a decent training in statistical methodology.

3. This is not an empirical fact based course. Sometimes there is no simple answer.

COURSE-LEVEL EDUCATIONAL GOALS:

The Course
You are expected to know the material presented in lecture and tutorial. This material is supported by various other sources, notably readings that will be placed in the copier room on an as needed basis and outlines handed out in class.

4. Assignments: You will carry out SPSS analyses and answer questions. Although the assignments are more applied in nature, I will, occasionally, include a logical question. These assignments are supposed to be challenging. You will be working with real data and typically inventing solutions to tricky problems. How you state your conclusions does matter (i.e, competent writing will be rewarded).

Note: Late assignments will receive a mark of zero.

5. Exams: 1 Midterm (October 29), 1 Final (December 12)

- 3 to 5 short essay.

- How you state your opinions matters.

-The final is not cumulative

6. The assignment of marks will be according to the following scheme:

4 Assignments 40%

1 Midterm 30%

1 Final 30%

The grade categories are as follows:

A+ 90+

A 85-

A- 81-

B+ 77-

B 74-

B- 71-

C+ 67-

C 64-

C- 59-

D 50-

F 0-

6. T.A.

Grading

NOTES:

Psy301

Tentative Schedule

Sept 10. Lect1 Data Analysis and Logic of Statistical Inference (Assignment 1 out)

Sept 17. Lect2 Logic of Statistical Inference

Sept 24. Lect3 Logic of Statistical Inference

Oct 1. Lect4 Logic of Statistical Inference (Assignment 2 out)

Oct 8. Thanksgiving. no class. Assignment 1 due by Wednesday,

10th, 4:00p.m., RCB6152

Oct. 15 Lect5 directionality , illogicalities

Oct. 22 Lect6 Concept of Relationship

Oct. 29 Lect 7 Midterm

Nov. 5. Lect 8 1-factor b.s. design (relationship between continuous d.v.

and nominal i.v.) (Assignment 3 out)

Nov. 12 Remembrance Day. no class. Assignment 2 due by Wednesday,

14th, 4:00p.m., RCB6152

Nov. 19 Lect 9 relationship for 2 QC variables (Assignment 4 out)

Nov. 26. Lect 10 p-way b.s. design (relationship between continuous d.v. and

set of nominal i.v.s) Assignment 3 due in class

December 3. Lect 11

-----------------------------------

December 10. Assignment 4 due: 4:00p.m., RCB6152

December 12. Final Exam. 8:30-11:30

Registrar Notes:

SFU’s Academic Integrity web site http://students.sfu.ca/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS