Multivariate Analysis

This micro-credential will cover many common statistical techniques used to analyse high dimensional data. Topics include: clustering techniques; classification techniques; ordination techniques such as principal components analysis; and graphical techniques such as multidimensional scaling. All analyses will be conducted using the R software.

Accordion / FAQ component

Most micro-credentials require a 2.2 degree in a related discipline or equivalent professional experience. Should you have any queries regarding your eligibility, please contact us at

N.B. Required basic statistics modules covering e.g. hypothesis testing, inference, regression, maximum likelihood. Elementary matrix algebra including eigenvalues and eigenvectors.

The learner will be familiarised with the basic multivariate techniques and where their use is appropriate. The learner will develop skills to conduct an analysis of multivariate data using statistical software, interpret the results and draw conclusions. The learner will be made aware of the advantages and limitations of each method.

Indicative  Content:

  • Introduction to multivariate data.
  • Mathematical necessities.
  • Clustering
  • Classification
  • Multidimensional scaling
  • Principal components analysis
  • Factor analysis

Learn from world renowned academic staff in Ireland’s leading, future focused and globally recognised colleges.

Gain an accredited NFQ qualification/micro credential that you may count towards a full award if you so wish in the future.

Previous modules may be used as recognition of prior learning towards Advance Centre degree programmes.

Equip yourself with the latest in demand skillset, tools, know-how and knowledge to succeed in your career.

Gain a competitive edge, influence growth and steer strategic goals in your organisation upon completion of your studies with the Advance Centre.

Yes, if you complete this micro-credential it can be credited as part of the MSc Data Analytics 

Detailed Course Information

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