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Course objectives:
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The topic of the course are linear statistical models. The aim is to connect students existing knowledge of parametric statistics and to show these methods can be perceived as special cases of linear model. Students gain skills of a flexible and confident use of linear models to solve complex statistical problems.
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Requirements on student
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Assignments during the semester. Practical exam.
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Content
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Simple regression and its graphical representation
Standardized regression coefficients
Overall accuracy of the model
Multiple regression
General linear model, categorical variables
Interactions
Examination of nonlinear relationships
Statistical significance tests
Assumptions of linear models
Stepwise and hierarchical regression
Removing the effect of variable, residuals
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Activities
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Fields of study
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Guarantors and lecturers
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Literature
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Homework for Teaching
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30
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Attendace
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4
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Preparation for the Exam
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20
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Total
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54
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| Prerequisites - other information about course preconditions |
| Knowledge of descriptive statistics and bacis tests of null hypotheses. |
| Competences acquired |
| Ability to design a statistical model, to estimate its parameters, to evaluate its quality, to perform related statistical tests, and to check its assumptions. The emphasis is on practical application of acquired skills in the context of psychological research is held. |
| Teaching methods |
- Monologic Lecture(Interpretation, Training)
- Projection (static, dynamic)
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| Assessment methods |
- Student performance
- Seminar Work
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