| Unit name | Multivariate Statistical Methods in Education |
|---|---|
| Unit code | EDUCM5507 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Academic Year (weeks 1 - 52) |
| Unit director | Professor. Martin Hughes |
| Open unit status | Not open |
| Pre-requisites |
None |
| Co-requisites |
None |
| School/department | School of Education |
| Faculty | Faculty of Social Sciences and Law |
The unit will introduce students to a range of statistical methods available in the statistical package SPSS for Windows, with the main emphasis being on the use of advanced statistics and their interpretation. The philosophy of the course is that students learn more about inferential statistics by carrying them out using a real data set than by trying to learn statistical theory from first principles. Statistics covered include: analysis of variance and covariance, simple and multiple linear regression, multivariate techniques of factor analysis, discriminant analysis and cluster analysis, and the use of secondary data analysis in education.
Aims:
To provide students with a statistical understanding sufficient for them to be able to carry out, interpret and present statistical procedures correctly, and to have a critical appreciation of published statistics. Students will be provided with sufficient knowledge of SPSS to enable them to carry out these exercises but the emphasis of the course is on the understanding and interpretation of the statistics themselves rather than on acquiring a detailed knowledge of the computing procedures.
Students will gain a working knowledge of a range of essential multivariate inferential statistics available on SPSS. They will be able to select, apply and interpret these statistics appropriately according to research hypotheses and the scale of measurement of the variables involved. They will consider the use and value of secondary analyses of existing data sets in education.
Students carry out set exercises using a prepared data set followed by group discussion of the results. Explanations of the theoretical premises underlying the statistical methods are provided by the tutor verbally and through printed materials and worksheets.
The needs of a wide range of students, including those with disabilities, international students and those from ethnic minority backgrounds have been considered. It is not anticipated that the teaching and assessment methods used will cause disadvantage to any person taking the unit. The Graduate School of Education is happy to address individual support requests as necessary.
Students carry out a statistical analysis using SPSS with a prepared data set provided by the tutor. Each analysis is preceded by a short account of the research background, and followed by a critical interpretation of the results. These analyses together form a report (equivalent to around 4,000 words) which is submitted as one 20 credit assessment.
Main Course Text:
Field A (2005) Discovering Statistics Using SPSS (2nd Edition) London, Sage
Alternative Texts:
Bryman, A. and Cramer, D. (2005) Quantitative Data Analysis with SPSS 12 and 13: a guide for Social Scientists. London: Routledge
Erickson, B.H. and Nosanchuk. T.A. (1992) Understanding Data, Buckingham: Open University Press
McCall, R.B. (2001) Fundamental Statistics for Behavioural Sciences, Belmont, California: Wadsworth
Siegel, S. and Castellan N.J. (1988) Nonparametric Statistics for the Behavioural Sciences, New York: McGraw-Hill
Wright, D.B. (1997) Understanding Statistics: An introduction for the social sciences, London: Sage
