Quantitative Methods

University of Otago

Course Description

  • Course Name

    Quantitative Methods

  • Host University

    University of Otago

  • Location

    Dunedin, New Zealand

  • Area of Study


  • Language Level

    Taught In English

  • Prerequisites

    ((PSYC 201 and PSYC 202) or (PSYC 201 and PSYC 210 and PSYC 212) or (PSYC 202 and PSYC 211) or (PSYC 210 and PSYC 211 and PSYC 212)) and (STAT 110 or STAT 115)

  • Course Level Recommendations


    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • Credit Points

  • Recommended U.S. Semester Credits
    3 - 4
  • Recommended U.S. Quarter Units
    4 - 6
  • Overview

    Design and analysis of psychological experiments.

    In this course, students learn how to analyse research data using the general linear model. This model is the basis for most commonly used statistical techniques in psychological research, including analysis of variance (ANOVA), correlation and regression. Students will gain a conceptual understanding of what the model is, how it is used to analyse data and what it teaches us about how research studies should be designed in the first place.

    Course Structure
    -Analysis of experimental data: analysis of variance
    -Describing experimental designs
    -Analysis of between-subjects designs: one-way, two-way, three-way, etc
    -Analysis of within-subjects designs (repeated-measures): one-way, two-way, three-way, etc
    -Analysis of mixed designs

    [In-class test]
    -Correlation and simple regression
    -Fitting a predictive model
    -Hypothesis testing
    -Inferences about causality
    -Regression toward the mean
    -Multiple regression
    -Fitting a multiple-regression model
    -Testing the full model
    -Testing individual terms in the model: the extra sum of squares principle
    -Model selection procedures (all possible, forward, backward, stepwise)

    -Dummy variable regression and analysis of covariance
    -Effects coding
    -Using dummy variables to perform ANOVA
    -Relationship of dummy variable regression to ANOVA
    -Dummy variable regression for ANOVA with unequal cell sizes
    -The mechanics of ANCOVA
    -ANCOVA for error reduction
    -ANCOVA for statistical control

    Required Calculator: Students require calculators for this paper. For the test and examination, students may use any calculator without communication capabilities.

    Weekly homework exercises 20%
    Computer competency exam 5%
    Test 25%
    Final examination 50%

    Learning Outcomes
    Demonstrate ability to understand, apply and interpret advanced statistical techniques used in scientific research in psychology

    Required Reading: Miller, J., & Haden, P. (2013). Statistical analysis with the general linear model

Course Disclaimer

Courses and course hours of instruction are subject to change.

Eligibility for courses may be subject to a placement exam and/or pre-requisites.

Some courses may require additional fees.

Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.

Please reference fall and spring course lists as not all courses are taught during both semesters.

Availability of courses is based on enrollment numbers. All students should seek pre-approval for alternate courses in the event of last minute class cancellations

Please note that some courses with locals have recommended prerequisite courses. It is the student's responsibility to consult any recommended prerequisites prior to enrolling in their course.