Extended data for Bases of Data Analyses in the Cognitive Field

Bases of Data Analyses in the Cognitive Field

Institution

Eötvös Loránd University

Organizational Unit

PPK Institute of Psychology

Related programme

Psychology

Code

PSZM21-MO-KOGN-102

ECTS

4

ISCED code

0313 Psychology

Language of instruction

English

Academic term

1/2

Title

Bases of Data Analyses in the Cognitive Field hu

Bases of Data Analyses in the Cognitive Field en

Content of the course Topic of the course Which type of software to choose Analyzing behavioral data Diffusion model analysis Hypothesis tests The reasoning behind the tests and the main consequences Bayesian and frequentist solutions Automatic data analysis Bases of data manipulation Spreadsheet Reliability in cognitive areas Descriptives Describing a single variable Describing the relation of two variables, fitting functions Statistical simulations Monte Carlo and bootstrapping methods Statistical analysis with computer programming Learning activities, learning methods Hands-on analyses Data analyses homework

Content of the course Topic of the course Which type of software to choose Analyzing behavioral data Diffusion model analysis Hypothesis tests The reasoning behind the tests and the main consequences Bayesian and frequentist solutions Automatic data analysis Bases of data manipulation Spreadsheet Reliability in cognitive areas Descriptives Describing a single variable Describing the relation of two variables, fitting functions Statistical simulations Monte Carlo and bootstrapping methods Statistical analysis with computer programming Learning activities, learning methods Hands-on analyses Data analyses homework

Evaluation of outcomes Learning requirements, mode of evaluation and criteria of evaluation: Data analysis related practical task. The students are offered a series of types of tasks (e.g., reanalyzing former data with new methods) and they can choose between the tasks depending on which task fits their learning goals the most. Mode of evaluation:  practical evaluating the submitted project work Criteria of evaluation: Approriateness of the solution provided for the data analysis task

Evaluation of outcomes Learning requirements, mode of evaluation and criteria of evaluation: Data analysis related practical task. The students are offered a series of types of tasks (e.g., reanalyzing former data with new methods) and they can choose between the tasks depending on which task fits their learning goals the most. Mode of evaluation:  practical evaluating the submitted project work Criteria of evaluation: Approriateness of the solution provided for the data analysis task