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).
The course will involve a number of instructional methods, such as the following:
2. Online videos
3. Group discussion
Evaluation will be carried out in accordance with Douglas College 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%
At the conclusion of the course students will be able to:
Understand and make effective use of descriptive statistics for different analyses.
Compare basic data types and identify the limitations they pose on statistical analyses.
Demonstrate understanding of suitable ways to identify and deal with missing values in a data set.
Describe appropriate methods of data security.
Identify proper data structure and data coding.
Use widely available software tools to analyze and present results of research.
Assess psychometric properties of scales.
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. (1992). Introduction to Design & Analysis: A Student’s Handbook (2nd Ed.). Worth.
- Gliner, J.A., Morgan, G.A., & Leech, N.L. (2009). Research methods in applied settings: An integrated approach to design and analysis (2nd ed.). New York, NY: Taylor-Francis.
- Howell, D. C. (2010). Statistical methods for psychology (7th ed.). Pacific Grove, CA: Thompson-Wadsworth.
- SPSS Student Software (also available in DC computer labs)
- IBM SPSS Statistics User Manual (free online)
PSYC 1100 AND 1200, both with a C- or better
Courses listed here must be completed either prior to or simultaneously with this course:
- No corequisite courses
Courses listed here are equivalent to this course and cannot be taken for further credit:
- No equivalency courses
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.
|Institution||Transfer Details||Effective Dates|
|Kwantlen Polytechnic University (KPU)||KPU PSYC 3XXX (3)||2012/01/01 to -|
|Langara College (LANG)||LANG PSYC 3200 (3)||2012/01/01 to -|
|Simon Fraser University (SFU)||SFU GE 1XX (3)||2012/01/01 to -|
|Thompson Rivers University (TRU)||TRU PSYC 3XXX (3)||2012/01/01 to -|
|University Canada West (UCW)||UCW RSCH 300 (3)||2012/01/01 to 2016/12/31|
|University Canada West (UCW)||UCW PSYC 3XX (3)||2017/01/01 to -|
|University of British Columbia - Okanagan (UBCO)||UBCO PSYO 2nd (3)||2012/01/01 to -|
|University of British Columbia - Vancouver (UBCV)||UBCV COMM 2nd (3)||2012/01/01 to -|
|University of Northern BC (UNBC)||UNBC PSYC 3XX (3)||2012/01/01 to -|
|University of the Fraser Valley (UFV)||UFV BUS 320 (3)||2012/01/01 to -|
|University of Victoria (UVIC)||UVIC PSYC 2XX (1.5)||2012/01/01 to -|