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PSYC434 Advanced Quantitative Methods

Introduction to a variety of advanced statistical methods used in psychology.

A practical introduction to a broad range of sophisticated statistical concepts and techniques used in psychological research. The emphases are on identifying research scenarios in which each concept or technique should be considered and on using SPSS to extract insights from a given data set.

Paper title Advanced Quantitative Methods
Paper code PSYC434
Subject Psychology
EFTS 0.0833
Points 10 points
Teaching period First Semester
Domestic Tuition Fees (NZD) $653.49
International Tuition Fees (NZD) $2,757.23

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Restriction
PSYC 461
Contact

Professor Jeff Miller (miller@psy.otago.ac.nz)

Teaching staff

Professor Jeff Miller

Textbooks

Course material will be provided electronically via Blackboard. Students should ensure that they know their user names and passwords and can access Blackboard before the start of classes.

Graduate Attributes Emphasised
Interdisciplinary perspective, Lifelong learning, Critical thinking, Information literacy.
View more information about Otago's graduate attributes.
Paper Structure

The paper will undertake a wide-ranging survey of statistical concepts and methods. Initially, fundamental statistical concepts will be re-examined within the context of ongoing controversies surrounding common statistical practices. Then, a wide range of advanced statistical techniques will be examined, focusing on (1) different types of questions that can be addressed; (2) types of data needed to address them; (3) how analyses can be conducted using SPSS; and (4) what the results mean.

PSYC 434 Paper Outline

The paper consists of a series of lectures, practical computer exercises, and homework exercises designed to give students both theoretical understanding of and practical experience with a range of advanced data analysis techniques including:

  • Fundamental issues in hypothesis testing and replicability
  • Categorical data analysis
  • Nonparametric methods
  • Logistic regression
  • Factor analysis
  • MANOVA
  • Multidimensional scaling
  • Computer simulation
  • Bootstrapping, Jackknifing, and permutation testing
  • Meta-analysis

Students will carry out the homework assignments in pairs, pairing up with each individual partner no more than twice (enrolment permitting).  Experience has shown that students learn much about the topics from these pairwise interactions. They also learn about how to work together with a colleague when analysing data, which is useful because most real-world research projects are analysed collaboratively.

Assessment:

  • Homework assignments 50%
  • Examination (2 hours) 50%
Eligibility

Entry into Psychology 400-level normally requires a major in Psychology, a B+ average or higher in Psychology 300-level papers, and a pass in PSYC 311 Quantitative Methods. We highly recommend that students have completed PSYC 310. Students from other universities must show evidence of an equivalent level of competence.

Learning Outcomes
  1. Understand how a variety of statistical techniques may be used in a range of experimental and applied situations (Information Literacy, Research).
  2. Assess the suitability of a variety of statistical techniques for the analysis of different types of data sets (Critical Thinking, Research).
  3. Evaluate the extent to which individual data sets satisfy the assumptions underlying different statistical techniques (Critical Thinking, Information Literacy).
  4. Independently select and apply an appropriate data analysis technique to answer a given research question; interpret the results of the analysis as they bear on that question (Communication, Critical Thinking, Research, Self- Motivation).

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Timetable

First Semester

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

Lecture

Stream Days Times Weeks
Attend
A1 Tuesday 13:00-13:50 9-16, 18-22
Thursday 11:00-11:50 9-16, 18-22