Intermediate SPSS
Presenters: Dr. Juliet Harman, Dr. Leslie Humphreys and Dr. Svetlana Tishkovskaya
This course builds on previous introductory courses to cover more advanced techniques of statistical analysis. The principles of statistical inference are reviewed and applied to the general linear model. This framework is then extended to a wider class of statistical models, including non-linear, multivariate and non-normal models. The general principles of model selection and hypothesis testing are illustrated in each case by application to substantive issues in real data examples.
Cost
- Lancaster University staff and postgraduates - £50
- External staff member from an academic institution on a NODE course - £120
- External Postgraduate research student from an academic institution on a NODE course - £60
- External participant from a non academic institution on a NODE course - £440
The course fees include all supporting documentation, refreshments and lunches.
Topics
Topics covered will be: General methodology for linear models: ANOVA and ANACOVA models Extensions to: non-linear models, factor analysis, logistic regression, log-linear models and the analysis of duration data.
Learning
Students will learn through the application of concepts and techniques covered in the course to real data sets. Students will be encouraged to examine issues of substantive interest in these studies.
Successful students will be able to:
- perform advanced statistical procedures
- identify the appropriate procedure for a particular substantive issue
- apply theoretical concepts
- identify and solve problems
- analyse data and interpret statistical output
- apply strategies for appropriate selection of information
