EDUC9766 Multivariate statistics for educational research

2016

4.5

1 x 2-hour workshop weekly

1 EDES9003 - Introduction to Educational Statistics
1a EDES9003D - Introduction to Educational Statistics
1b EDUC9762 - Introduction to Statistics
Must Satisfy: ((1 or 1a or 1b))

1 of EDES9005, EDES9005D has been successfully completed

Students should be familiar with Excel and SPSS or similar programs.

This topic is designed for students who wish to understand and use advanced statistical techniques. The topic aims to prepare students in education to select and employ appropriate analytical procedures for the examination of data collected in surveys, quasi-experimental research studies and longitudinal studies, as well as to draw appropriate conclusions and interpret the research findings from such studies. The topic concentrates on the understanding and use of the analytical procedures of linear and multiple regression, and data reduction techniques. Multilevel regression and structural equation modelling are introduced. The programs SPSS, AMOS and HLM are used. A central goal of the topic is to enable students to evaluate critically contemporary educational research and to contribute to that research.

Students will:

• understand the assumptions underlying multivariate techniques and be aware of the limitations of these techniques in complex survey and longitudinal studies

• understand multivariate and multilevel methods and know when and how to apply them

• be able to use standard statistical software to conduct multivariate and multilevel analyses

• be able to write interpretive reports in which the results of multivariate and multilevel analyses are accessible to non-specialists

On completion of this topic students will be able to:

• perform multivariate estimation and hypothesis testing

• use exploratory data reduction techniques, such as principal component analysis and factor analysis, and confirmatory factor analysis

• describe the assumptions and limitations of multivariate statistical techniques used to in the analysis of complex educational survey data

• select and justify appropriate multivariate and multilevel techniques to address an educational problem

• use standard statistical programs to analyse complex survey data sets to answer educational problems

• write interpretive reports demonstrating appropriate use, interpretation and communication of multivariate and multilevel statistical results for non-specialist audiences