Multivariate Statistics

Course code

IFI7071.DT

old course code

IFI7071

Course title in Estonian

Mitmemõõtmeline statistika

Course title in English

Multivariate Statistics

ECTS credits

6.0

Assessment form

Examination

lecturer of 2022/2023 Autumn semester

Not opened for teaching. Click the study programme link below to see the nominal division schedule.

lecturer of 2022/2023 Spring semester

Not opened for teaching. Click the study programme link below to see the nominal division schedule.

Course aims

To create opportunities for acquiring theoretical knowledge and practical skills for understanding some most popular multivariate models used in social sciences. Applying these techniques with the aid of statistical software SPSS.

The course is specially set up to support developing ones ability to interpret the results of statistical techniques.

The course is specially set up to support developing ones ability to interpret the results of statistical techniques.

Brief description of the course

Factorial ANOVA, MANOVA, linear regression, logistic regression, cluster analysis, factor analysis, discriminant analysis, multidimensional scaling.

Course consists of video lectures and practical classes where students are expected to be actively involved. In addition every student must submit home assignment, where (s)he demonstrates the command of all statistical data analysis techniques presented in the course.

Course consists of video lectures and practical classes where students are expected to be actively involved. In addition every student must submit home assignment, where (s)he demonstrates the command of all statistical data analysis techniques presented in the course.

Learning outcomes in the course

Upon completing the course the student:

- understands the basic underlying assumptions of multivariate statistics;

- has got experience in setting up questions about data which lead to multivariate analysis of the differences and relationships;

- understands statistical concepts introduced during the course, knows the prerequisites for their correct application and can interpret the results of the analysis correctly;

- can recognise different types of variables and choose appropriate statistical techniques accordingly;

- can use the SPSS software with the aid of the manual for composing multivariate models introduced in the course.

- understands the basic underlying assumptions of multivariate statistics;

- has got experience in setting up questions about data which lead to multivariate analysis of the differences and relationships;

- understands statistical concepts introduced during the course, knows the prerequisites for their correct application and can interpret the results of the analysis correctly;

- can recognise different types of variables and choose appropriate statistical techniques accordingly;

- can use the SPSS software with the aid of the manual for composing multivariate models introduced in the course.

Teacher

Kairi Osula

The course is a prerequisite

Study programmes containing that course

Mathematics, Mathematical Economics and Data Analysis (MLMB/22.DT)

Well-Being and Health Behaviour (TSTM/22.LT)

Psychology (PSPSM/22.LT)

Mathematics, Mathematical Economics and Data Analysis (MLMB/21.DT)

Psychology (PSPSM/21.LT)

Mathematics, Mathematical Economics and Data Analysis (MLMB/20.DT)

Well-Being and Health Behaviour (TSTM/21.LT)

Psychology (PSPSM/20.LT)

Well-Being and Health Behaviour (TSTM/20.LT)

Mathematics, Mathematical Economics and Data Analysis (MLMB/19.DT)

Mathematics, Mathematical Economics and Data Analysis (MLMB/18.DT)

Psychology (PSPSM/19.LT)

Psychology (PSPSM/18.LT)

Psychology (PSPSM/17.LT)

Psychology (PSPSM/16.LT)

Psychology (PSPSM/15.LT)

Psychology (PSPSM/14.LT)

Psychology (PSPSM/13.LT)

Psychology (PSPSM/12.LT)

Psychology (PSPSM/12-3.LT)

Psychology (PSPSM/12-2.LT)

Well-Being and Health Behaviour (TSTM/22.LT)

Psychology (PSPSM/22.LT)

Mathematics, Mathematical Economics and Data Analysis (MLMB/21.DT)

Psychology (PSPSM/21.LT)

Mathematics, Mathematical Economics and Data Analysis (MLMB/20.DT)

Well-Being and Health Behaviour (TSTM/21.LT)

Psychology (PSPSM/20.LT)

Well-Being and Health Behaviour (TSTM/20.LT)

Mathematics, Mathematical Economics and Data Analysis (MLMB/19.DT)

Mathematics, Mathematical Economics and Data Analysis (MLMB/18.DT)

Psychology (PSPSM/19.LT)

Psychology (PSPSM/18.LT)

Psychology (PSPSM/17.LT)

Psychology (PSPSM/16.LT)

Psychology (PSPSM/15.LT)

Psychology (PSPSM/14.LT)

Psychology (PSPSM/13.LT)

Psychology (PSPSM/12.LT)

Psychology (PSPSM/12-3.LT)

Psychology (PSPSM/12-2.LT)