Course

Applied Data Analysis in Psychology

Faculty
Humanities & Social Sciences
Department
Psychology
Course Code
PSYC 3301
Credits
3.00
Semester Length
15
Max Class Size
35
Method(s) Of Instruction
Hybrid
Lecture
Lab
Course Designation
None
Industry Designation
None
Typically Offered
To be determined

Overview

Course Description
The purpose of this course is to teach students how to analyze data using current data analysis computer software. The course covers major analytic methods, as well as methods appropriate to dealing with missing values, and analyzing the psychometric properties of scales. Students will analyze a number of datasets using XLSTAT and/or SPSS. Emphasis will be placed on generating results and interpreting results appropriately, not statistical theories. Upon completion of this course, students should be able to prepare datasets for analysis, and conduct a wide range of descriptive and inferential analyses of data.
Course Content

The topics covered may include:

1. Data structure: How are data files structured? What types of data files are there? How should data providers be instructed to enter data so that it is in an analyzable form?

2. Data coding: How should data be coded to maximize the efficiency of analysis?

3. Data auditing: What are the issues with data accuracy? How should data be audited to ensure accuracy?

4. Data security: How should data files be securely managed? What information should and should not be included in shared data files? How is anonymity and confidentiality ensured?

5. Data preparation: How should missing and out of range values be identified? What should be done with missing and out of range values? What are the various analytic methods of dealing with missing values (multiple regression, nearest neighbour PCA)?

6. Recoding: What is recoding? What are the issues with recoding data? What are the basic methods of recoding?

7. Data types: What are the basic data types (ordered vs. unordered, continuous vs. discrete, ranks, metric vs. non-metric)? How does data type influence the sorts of analyses that should be conducted on the data?

8. Univariate descriptive statistical analysis: What are the basic univariate descriptive statistics that should be calculated on data (distributions, central tendency, variability, kurtosis, graphical representation)?

9. Bivariate and multivariate descriptive statistics: What are the basic bivariate and multivariate statistics that should be calculated on data (conditional distributions, centroids, covariance, linear and non-correlation, correlation matrices, multi-dimensional scaling, PCA, multivariate graphical representation)?

10. Hypothesis tests of mean differences: t-test for dependent and independent groups, one-way ANOVA, factorial ANOVA.

11. Regression: Bivariate regression, multiple regression.

12. Tests of the psychometric properties of scales: Tests for homogeneity and unidimensionality of items (Cronbach's Alpha and linear factor analysis).

 

Learning Activities

The course will involve a number of instructional methods, such as the following:

  • Lecture
  • Online videos
  • Group discussion
  • Lab
Means of Assessment

Evaluation will be carried out in accordance with the Douglas College Evaluation Policy. Evaluation will be based on course objectives and will include some of the following: quizzes, multiple choice exams, essay type exams, term paper or research project, computer based assignments, etc. The instructor will provide the students with a course outline listing the criteria for course evaluation.

Grading in the course will be a combination of at least 3 analysis assignments and/or tests. An example of one evaluation scheme:

1 exam: 30%

5 computer-based assignments: 70%

Total: 100%

Learning Outcomes

At the conclusion of the course, successful students will be able to:  

  1. Understand and make effective use of descriptive statistics for different analyses; 
  2. Compare basic data types and identify the limitations they pose on statistical analyses; 
  3. Demonstrate understanding of suitable ways to identify and deal with missing values in a data set; 
  4. Describe appropriate methods of data security;
  5. Identify proper data structure and data coding;
  6. Use widely available software tools to analyze and present results of research;
  7. Assess psychometric properties of scales.
Textbook Materials

Textbooks and Materials to be Purchased by Students:

Textbook(s) and materials such as the following, the list to be updated periodically:

  • Freeman, W. H.; Keppel, G.; Saufley, W. H. Jr.; Tokunaga, H.  Introduction to Design & Analysis: A Student’s Handbook (Current ed.). Worth.
  • Gliner, J.A., Morgan, G.A., & Leech, N.L.  Research methods in applied settings: An integrated approach to design and analysis (Current ed.). New York, NY: Taylor-Francis.
  • Howell, D. C.   Statistical methods for psychology (Current ed.). Pacific Grove, CA: Thompson-Wadsworth.
  • SPSS Student Software (also available in DC computer labs)
  • IBM SPSS Statistics User Manual (free online)

Requisites

Prerequisites

PSYC 1100 AND PSYC 1200, both with a C- or better

AND

PSYC 2300 with a C or better AND one of PSYC 2301 OR CRIM 2254 with a C or better

AND

Admission to the Bachelor of Arts in Applied Psychology Program or the Bachelor of Arts in Applied Psychology Honours Program or Bachelor of Arts  in Applied Criminology or Bachelor of Arts in Applied Criminology-Honours or Psychology (Minor) Program or with permission of the instructor.

Corequisites

No corequisite courses.

Equivalencies

No equivalent courses.

Course Guidelines

Course Guidelines for previous years are viewable by selecting the version desired. If you took this course and do not see a listing for the starting semester / year of the course, consider the previous version as the applicable version.

Course Transfers

These are for current course guidelines only. For a full list of archived courses please see https://www.bctransferguide.ca

Institution Transfer Details for PSYC 3301
Kwantlen Polytechnic University (KPU) KPU PSYC 3XXX (3)
Langara College (LANG) LANG PSYC 3200 (3)
Simon Fraser University (SFU) SFU GE 1XX (3)
Thompson Rivers University (TRU) TRU PSYC 3XXX (3)
University Canada West (UCW) UCW PSYC 3XX (3)
University of British Columbia - Okanagan (UBCO) UBCO PSYO_O 2nd (3)
University of British Columbia - Vancouver (UBCV) UBCV COMM_V 2nd (3)
University of Northern BC (UNBC) UNBC PSYC 3XX (3)
University of the Fraser Valley (UFV) UFV BUS 320 (3)
University of Victoria (UVIC) UVIC PSYC 2XX (1.5)

Course Offerings

Summer 2024

CRN
Days
Dates
Start Date
End Date
Instructor
Status
CRN
24478
Wed
Start Date
-
End Date
Start Date
End Date
Instructor Last Name
Jackson
Instructor First Name
Jeremy
Course Status
Open
Max
Enrolled
Remaining
Waitlist
Max Seats Count
35
Actual Seats Count
29
6
Actual Wait Count
0
Days
Building
Room
Time
Wed
Building
New Westminster - North Bldg.
Room
N6105
Start Time
15:30
-
End Time
18:20