Data Analysis in Psychology

Faculty
Humanities & Social Sciences
Department
Psychology
Course Code
PSYC 2300
Credits
3.00
Semester Length
15
Max Class Size
35
Method Of Instruction
Lecture
Typically Offered
To be determined
Campus
Online

Overview

Course Description
This course introduces students to the concepts and applications of statistics and focuses on the analysis and interpretation of data from experiments and surveys using descriptive and inferential statistics. Computerized data analysis is also introduced.
Course Content
  1. Abuses of statistics
  2. Organizing and describing data
  3. Measures of central tendency
  4. Measures of variability
  5. Standard scores
  6. Description of frequency distributions
  7. Properties of normal distributions
  8. Central Limit Theorem
  9. Introduction to probability concepts
  10. Null hypothesis significance testing
  11. Analysis of Variance and t-tests
  12. Correlation methods
  13. Regression and prediction
  14. Nonparametric statistical methods
  15. Statistical significance versus practical importance
  16. Measures of effect size and confidence intervals
Methods Of Instruction

This course will employ a number of instructional methods to accomplish its objectives and will include some of the following: 

  • lectures
  • audio visual materials
  • small group discussion
  • research projects
  • computer based tutorial exercises
Means of Assessment

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. 

An example of one evaluation scheme:

12 quizzes  40%
Computer based homework assignments      10%
Homework exercises  10%
Midterm exam  20%
Final exam  20%
Total 100%
Learning Outcomes

At the conclusion of the course the successful student will be able to:

  1. Define, describe and distinguish between descriptive and inferential statistics, and identify in what contexts each is appropriate.
  2. Define, describe, distinguish between, and demonstrate ability to calculate, by hand and/or using statistical software, various key descriptive statistical terms, such as: empirical distribution, frequency distribution, histogram, percentile, quartile, measures of central tendency (median, mode, mean), sum of squares, measures of variance (range, variance, standard deviation, within-groups variance, between-groups variance), standard score/z-scores, covariance, Pearson r, regression coefficient, model, and effect size (e.g., Cohen’s d, Eta squared). 
  3. Define, describe, distinguish between, and demonstrate ability to calculate, by hand and/or using statistical software, various key research designs and inferential statistical terms, such as: scales of variables (nominal, ordinal, interval, ratio),  independent variable (IV), dependent variable (DV), theoretical distribution, population, sample, statistic, random sampling, estimator, estimate, probability distribution, parameter, normal distribution, t distribution, F-distribution, Chi-square distribution, sampling distribution, null hypothesis significance testing (NHST), null hypothesis, alternative hypothesis, p-value, alpha, beta, power, type 1 error, type 2 error, critical value, statistical significance, and confidence interval.
  4. Describe and explain the logic of inferential statistics. This includes being able to explain what a p-value is, what statistical significance means, and how various factors, such as sample size, effect size, alpha and violation of assumptions, influence the p-value and statistical significance.
  5. Calculate, interpret, explain the rationale for, and analyze the assumptions for appropriate test statistics and p-values for situations such as the following: a) there is one IV that has two or more levels and the DV is a scale variable – the IV may be a between or within subjects IV, b) there may be a linear relationship between two variables and the null hypothesis is that the population relationship is 0, c) there are observed frequencies for one or two variables and the null hypothesis is that the distribution of observed frequencies is non-proportional.
  6. Interpret basic research results as published in academic journals.
Textbook Materials

Textbook(s) such as the following, the list to be updated periodically.

  • Aron, A., Coups, E.J., & Aron, E. N. (2013) Statistics for psychology (6th ed.) Upper Saddle River, NJ: Pearson Education.
  • Howell, D. C. (2017) Fundamental statistics for the behavioral sciences (9th Ed.) Pacific Grove, CA: Brooks/Cole.
  • Gravetter, F.J., Wallnau, L.B. & Forzano, L.B. (2018). Essentials of statistics for the behavioral sciences (9th ed.). Boston, MA: Nelson/Cengage.

Requisites

Prerequisites

and

  • a C or better in Foundations of Math 11 or Pre-calculus 11 (or equivalent)

Corequisites

Courses listed here must be completed either prior to or simultaneously with this course:

  • No corequisite courses

Equivalencies

Courses listed here are equivalent to this course and cannot be taken for further credit:

  • No equivalency courses

Requisite for

This course is not required for any other course.

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

Institution Transfer Details Effective Dates
Athabasca University (AU) AU SOCI 301 (3) 2014/09/01 to -
Capilano University (CAPU) CAPU PSYC 213 (3) 2004/09/01 to -
Coast Mountain College (CMTN) CMTN PSYC 2XX (3) 2020/05/01 to -
College of New Caledonia (CNC) CNC PSYC 201 (3) 2004/09/01 to -
Coquitlam College (COQU) COQU PSYC 206 (3) 2004/09/01 to 2019/04/30
Kwantlen Polytechnic University (KPU) KPU PSYC 2300 (3) 2004/09/01 to -
Langara College (LANG) LANG PSYC 2321 (3) 2004/09/01 to -
Okanagan College (OC) OC PSYC 2XX (3) 2009/01/01 to -
Simon Fraser University (SFU) SFU PSYC 210 (3), Q 2004/09/01 to -
Thompson Rivers University (TRU) TRU PSYC 2100 (3) 2010/09/01 to -
Thompson Rivers University (TRU) TRU PSYC 210 (3) 2004/09/01 to 2010/08/31
Trinity Western University (TWU) TWU PSYC 207 (3) 2004/09/01 to -
University of British Columbia - Okanagan (UBCO) UBCO PSYO 271 (3) 2004/09/01 to -
University of British Columbia - Vancouver (UBCV) UBCV PSYC 218 (3) 2004/09/01 to -
University of Northern BC (UNBC) UNBC PSYC 315 (4) 2004/09/01 to -
University of the Fraser Valley (UFV) UFV PSYC 110 (3) or UFV STAT 104 (4) 2013/01/01 to -
University of the Fraser Valley (UFV) UFV PSYC 110 (3) or UFV MATH 104 (3) 2004/09/01 to 2012/12/31
University of Victoria (UVIC) UVIC PSYC 2XX (1.5) 2004/09/01 to 2016/08/31
University of Victoria (UVIC) UVIC PSYC 300A (1.5) 2016/09/01 to -
Vancouver Island University (VIU) VIU PSYC 204 (3) 2004/09/01 to -

Course Offerings

Fall 2020

CRN
Days
Dates
Start Date
End Date
Instructor
Status
Location
32240
Tue
08-Sep-2020
- 07-Dec-2020
08-Sep-2020
07-Dec-2020
Rochefort
Stephen
Waitlist
Online
This course will include synchronous on-line activities. Students should plan to be available on-line at scheduled course times.
Max
Enrolled
Remaining
Waitlist
35
35
0
7
Days
Building
Room
Time
Tue
14:30 - 17:20
CRN
Days
Dates
Start Date
End Date
Instructor
Status
Location
32241
Thu
08-Sep-2020
- 07-Dec-2020
08-Sep-2020
07-Dec-2020
Rochefort
Stephen
Waitlist
Online
This course will include synchronous on-line activities. Students should plan to be available on-line at scheduled course times.
Max
Enrolled
Remaining
Waitlist
35
35
0
11
Days
Building
Room
Time
Thu
9:30 - 12:20
CRN
Days
Dates
Start Date
End Date
Instructor
Status
Location
32783
Wed
08-Sep-2020
- 07-Dec-2020
08-Sep-2020
07-Dec-2020
Vittoz
Nicole
Waitlist
Online
PSYC 2300-003 – This course will include synchronous on-line activities. Students should plan to be available on-line at scheduled course times.
Max
Enrolled
Remaining
Waitlist
35
38
-3
5
Days
Building
Room
Time
Wed
10:30 - 12:20
CRN
Days
Dates
Start Date
End Date
Instructor
Status
Location
34242
Mon
08-Sep-2020
- 07-Dec-2020
08-Sep-2020
07-Dec-2020
Wilson
Scott
Waitlist
Online
This course will include synchronous on-line activities. Students should plan to be available on-line at scheduled course times.
Max
Enrolled
Remaining
Waitlist
35
37
-2
2
Days
Building
Room
Time
Mon
12:30 - 15:20
CRN
Days
Dates
Start Date
End Date
Instructor
Status
Location
34941
08-Sep-2020
- 07-Dec-2020
08-Sep-2020
07-Dec-2020
Wagner
Kristin
Waitlist
Online
PSYC 2300 090 is an online course.

All course activities will be asynchronous. Students will not be required to be online at specific scheduled times.
Max
Enrolled
Remaining
Waitlist
35
36
-1
4
CRN
Days
Dates
Start Date
End Date
Instructor
Status
Location
34942
08-Sep-2020
- 07-Dec-2020
08-Sep-2020
07-Dec-2020
Wagner
Kristin
Waitlist
Online
PSYC 2300 091 is an online course.

All course activities will be asynchronous. Students will not be required to be online at specific scheduled times.
Max
Enrolled
Remaining
Waitlist
35
37
-2
4