Multivariate Analysis is concerned with methods of analysing data that consist of observations on two or more variables for each individual or unit. Multivariate data will generally be correlated, and a wide variety of techniques are available to analyse these data. Many scientific disciplines make use of such techniques for investigating and better understanding large datasets.
During this course, commonly used multivariate techniques will be introduced and developed, and relationships between them examined. The emphasis of the course will be practical application and interpretation of results using a range of scientific related examples. Mathematical details are kept to a minimum.
For practical work, participants may choose to use the statistics package R, SAS, SPSS or Stata. Please note Stata users will need to use the freely available R software for practical work on partial least squares.
Who Should Attend?
Scientists and technologists involved in analysing multivariate data. A working knowledge of basic statistics and linear regression will be assumed, such as standard deviations and correlations, and simple and multiple linear regression.
How You Will Benefit
Participants will gain a sound practical understanding of commonly used multivariate techniques.
What Do We Cover?
Choice of Software
Practical work may be done in: R, SAS, SPSS, Stata
Note: For practical work, participants must bring their own laptop with a fully licensed version of their chosen software. Stata users will need to use the freely available R software for practical work on partial least squares.