Program Overview

EER502 Quantitative Research Methods

This subject is designed to introduce students to research methodologies and statistical procedures that are commonly used in quantitative research. As the central aim of the subject is to enable students to become informed and critical readers of research literature, the emphasis is on the purposes and constraints of selected statistical procedures. This requires an understanding of fundamental constructs that underpin data collection procedures and data analysis in quantitative research. Considerable emphasis is given to statistical procedures including univariate and bivariate analysis, as well as more sophisticated multivariate techniques. From this foundation, students are required to submit a proposal for quantitative research study, which asks students to identify a problem in the broad field of education, develop a research question or hypothesis, define the inherent constructs, select appropriate methods to investigate these constructs, and determine an analysis plan.

Availability

• Session 2 (60)
• Online
• Bathurst Campus

Subject Information

Grading System

HD/FL

Duration

One session

School

School of Education

Assumed Knowledge

EER500

Learning Outcomes

Upon successful completion of this subject, students should:

• be able to create experimental and quasi-experimental research designs
• be able to select statistical procedures which are appropriate for a range of commonly encountered research situations
• be able to analyse the quantitative aspects of recently published research on a variety of topics in education
• be able to critically evaluate the appropriateness of quantitative analyses in published research
• be able to analyse data using computer software

Syllabus

This subject will cover the following topics:

• An overview of quantitative research
• Levels of measurement: The meaning of variables
• Data entry and analysis in SPSS (Statistical Package for the Social Sciences)
• Distributions, means, standard deviations
• Sampling
• Structured interviews and surveys: Scale reliability and validity
• Power, effect size, significance, testing hypotheses, and errors
• Non-parametric tests
• Analysis of group means, including one-way ANOVA, factorial ANOVA, covariance and repeated measures
• Correlation and regression/multiple regression analysis
• Factor analysis
• Structural equation modelling