Multivariate Methods, 7.5 credits

Multivariata metoder, 7.5 hp

732G08

Main field of study

Statistics

Course level

First cycle

Course type

Single subject and programme course

Examiner

Ann-Charlotte Hallberg

Course coordinator

Ann-Charlotte Hallberg

Director of studies or equivalent

Jolanta Pielaszkiewicz
ECV = Elective / Compulsory / Voluntary
Course offered for Semester Weeks Language Campus ECV
F7KSA Bachelor´s Programme in Statistics and Data Analysis 5 (Autumn 2021) 202134-202143 Swedish Linköping, Valla E

Main field of study

Statistics

Course level

First cycle

Advancement level

G2F

Course offered for

  • Bachelor´s Programme in Statistics and Data Analysis

Entry requirements

  • General entry requirements for undergraduate studies
    and
    Social Studies, English and Mathematics corresponding to the level in Swedish upper secondary education (Samhällskunskap 1b or 1a1 and 1a2, Engelska 6, Matematik 3b or 3c)
  • 60 ECTS credits passed from semester 1 and 2 and at least 30 ECTS credits passed from semester 3 and 4 Bachelor´s Programme in Statistics and Data Analysis

Intended learning outcomes

Having completed the course, the student should be able to
- use knowledge about the most common multivariate methods
- display good understanding of major principles for interpretation and assessment of multivariate models
- use a standard statistical computer package to estimate and assess components from a given data set with multivariate methods
- verbally interpret the results from an analysis of multivariate models

Course content

The course provides basic skills for professional work with statistical problems with several correlated random variables.
Multivariate normal distributions. Distributions of quadratic forms. Confidence regions and test. Principal components
analysis. Factor analysis. Discriminant analysis. Cluster analysis. Canonical correlation. Multidimensional
scaling.

Teaching and working methods

Computer exercises in which the students have access to supervision provide practical experience of data analysis. The teaching comprises lectures and computer exercises.

Examination

The course is examined by exercises and by an oral or a written exam.

If the LiU coordinator for students with disabilities has granted a student the right to an adapted examination for a written examination in an examination hall, the student has the right to it. If the coordinator has instead recommended for the student an adapted examination or alternative form of examination, the examiner may grant this if the examiner assesses that it is possible, based on consideration of the course objectives.

Students failing an exam covering either the entire course or part of the course twice are entitled to have a new examiner appointed for the reexamination.

Students who have passed an examination may not retake it in order to improve their grades.

Grades

Three-grade scale, U, G, VG

Other information

Planning and implementation of a course must take its starting point in the wording of the syllabus. The course evaluation included in each course must therefore take up the question how well the course agrees with the syllabus. The course is carried out in such a way that both men´s and women´s experience and knowledge is made visible and developed.

Planning and implementation of a course must take its starting point in the wording of the syllabus. The course evaluation included in each course must therefore take up the question how well the course agrees with the syllabus. 

The course is carried out in such a way that both men´s and women´s experience and knowledge is made visible and developed.

Department

Institutionen för datavetenskap
Code Name Scope Grading scale
PRO1 Project 7.5 credits U, G, VG

Books

Manly B, Multivariate Method 4:e upplagan

ISBN: ISBN: 9781498728966

https://www.bokus.com/bok/9781498728966/multivariate-statistical-methods/

Compendia

Danielsson S, Grundläggande inferens vid multivariat normalfördelning

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