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Multivariate Statistics (SL_119)

About Study Course

Department: Statistics Unit
ECTS:3
Course supervisor:Andrejs Ivanovs
Study type:Part-Time, Full time
Course level:Master's
Target audience:Life Science
Language:Latvian
Study course description Full description, Part-Time, Full time
Branch of science:Mathematics; Theory of probability and mathematical statistics

Objective

The aim of the course is to introduce the tools and concepts of multivariate data analysis with a strong focus on applications with R program.

Prerequisites

Higher mathematics, probability, statistics, linear models, basic knowledge of R programming.

Learning outcomes

Knowledge

1.Student:
• has gained an in-depth knowledge of the theoretic probabilistic concepts related to multivariate analysis.
• illustrates the visualization techniques describing the multivariate data.
• assesses the most important multivariate techniques such as principal components analysis, factor analysis, cluster analysis and discriminant analysis.

Skills

1.• Implements appropriate multivariate data visualizations in R programme.
• Can independently apply multivariate data analysis techniques in R programme, to carry out research activities or highly qualified professional functions.

Competence

1.• Can compare and understand the aims of various multivariate data analysis methods and choose the most appropriate for the analysis of the data set.
• Can generate hypothesis and make analysis-based decisions related to multivariate data.

Study course planning

Planning period:Year 2024, Autumn semester
Study programmeStudy semesterProgram levelStudy course categoryLecturersSchedule
Biostatistics3Master'sRequiredMāris Munkevics
About Study CourseObjectivePrerequisitesLearning outcomesStudy course planning
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