Accessibility Skip to Global Navigation Skip to Local Navigation Skip to Content Skip to Search Skip to Site Map Menu

PSYC311 Quantitative Methods

Design and analysis of psychological experiments.

In this paper, 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.

Paper title Quantitative Methods
Paper code PSYC311
Subject Psychology
EFTS 0.1500
Points 18 points
Teaching period First Semester
Domestic Tuition Fees (NZD) $1,059.15
International Tuition Fees (NZD) $4,627.65

^ Top of page

Prerequisite
((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)
Schedule C
Arts and Music, Science
Notes
For Neuroscience students the prerequisite is PSYC 210 and (STAT 110 or STAT 115).
Teaching Arrangements
Three 1-hour lectures per week, with an optional additional 1-hour tutorial per week.
Textbooks
Required Reading:
Miller, J., & Haden, P. (2013). Statistical analysis with the general linear model
Graduate Attributes Emphasised
Communication, Critical thinking, Information literacy, Research.
View more information about Otago's graduate attributes.
Learning Outcomes
Students who successfully complete the paper will demonstrate the ability to understand, apply and interpret advanced statistical techniques used in scientific research in psychology.
Contact
miller@psy.otago.ac.nz
Teaching staff
Professor Jeff Miller
Paper Structure

Topics:

  • 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]
  • Regression
  • Correlation and simple regression
    • Scattergrams
    • 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.

Assessment:

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

^ Top of page

Timetable

First Semester

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Blackboard

Lecture

Stream Days Times Weeks
Attend
A1 Monday 11:00-11:50 9-16, 18-22
Wednesday 11:00-11:50 9-16, 18-22
Friday 11:00-11:50 9-15, 18-22