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Curricular information is subject to change
The student will be familiarised with the basic multivariate techniques and where their use is appropriate. The student will develop skills to conduct an analysis of multivariate data using statistical software, interpret the results and draw conclusions. The student will be made aware of the advantages and limitations of each method.Indicative Module Content:
Introduction to multivariate data.
Principal components analysis
|Student Effort Type||Hours|
|Specified Learning Activities||
|Autonomous Student Learning||
Basic statistics modules covering e.g. hypothesis testing, inference, regression, maximum likelihood. Elementary matrix algebra including eigenvalues and eigenvectors.
|Description||Timing||Component Scale||% of Final Grade|
|Continuous Assessment: Online assessments||Throughout the Trimester||n/a||Standard conversion grade scale 40%||No||
|Examination: Written exam||2 hour End of Trimester Exam||No||Standard conversion grade scale 40%||No||
|Resit In||Terminal Exam|
|Summer||Yes - 2 Hour|
• Group/class feedback, post-assessment
Not yet recorded.
|Ms Sinead Mcparland||Tutor|
|Mr John O'Sullivan||Tutor|