Essential Topics in Multivariate Data Analysis
School of study
Hertfordshire Business School
- Part Time
Prior knowledge of hypothesis testing and regression is essential.
About the course
This course is about some of the most commonly used multivariate data analysis techniques (factor, correspondence, cluster and discriminant analysis), focusing on the practical application of the techniques rather than their mathematical complexities.
This course is aimed at those who want to gain an understanding of some of the most commonly used multivariate analysis methods, namely factor analysis, correspondence analysis, cluster analysis and discriminant analysis. These techniques are used in a range of disciplines and examples used in the course will be accessible to all audiences including PhD students, researchers and those who need to use these techniques in the workplace. The use of a custom-built add-in for Microsoft Excel makes the analyses possible for all with even basic tools at their disposal.
The topics covered in this course are factor analysis (including principal components analysis), correspondence analysis, cluster analysis, discriminant analysis. These topics will be demonstrated using SPSS and a custom-built add-in for Microsoft Excel.
See our full range of courses at http://go.herts.ac.uk/sscu or contact the course organiser, Prof Neil Spencer, at email@example.com.
Dates can be organised if an organisation have a group of people wanting to take this course.