A. I. Cuza University of Iaşi

Multivariant Statistics

Course nameMultivariant Statistics CodeCS4103O1
Class Computer Science, 2004 - 2008 Package 6
Level Undergraduate Year 4 Semester 1 Status Optional
Hours per weekTotal hours per semesterTotal hours of individual workCreditsEvaluation typeTeaching language
CSLPr
2 0 2 0 56 0 6 E ro
Taught byAcademic and scientific title, name
Collaborator, Computer Scientist, Valentin Clocotici
Required courses
ObjectivesAfter completing this course students should be able to: understand and implement some common multivariate methods; correctly apply and interpret all of the statistical methods studied; choose an appropriate method for a given data set and problem; successfully communicate their findings to their peers; correctly interpret multivariate analyses in the scientific literature.
General thematicsPreparing & Cleaning Data

Analysis of variance (ANOVA) and covariance (ANCOVA)

Multiple Regression Analysis

Principle Components and Factor Analysis

Cluster Analysis

Seminary / Laboratory thematicsPracticals include:

  • using a statistical package like SPSS or Ms Excel Data Analysis
  • statistical analysis of multivariate datasets.
Exercises can be finished at home if needed.
Teaching methodsPowerPoint presentations and blackboard (if needed).
BibliographyLecture notes.

G. Mihoc, V. Urseanu, E. Ursianu: Modele de analiză statistică, Editura Ştiinţifică şi Enciclopedică, Bucureşti, 1982.

Evaluationconditions
criterias
modesThree (3) projects throughout the semester that will involve analyzing a data set and interpreting the findings; one literature review project; final exam (25 multiple choice items)
formulaPoints (maximum) = 3×30 (data analysis projects) + 20 (literature review project) + 40 (final exam) Final result is obtained by normalization.
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