SUBJECT

Data Analysis and Statistics

practical

master

Faculty of Education and Psychology

4

Semester 1

Autumn semester

Aim of the course:

By the end of the course one should be able to use advanced spreadsheet functions to analyse most of the cognitive data, and should understand basic concepts of the BA statistics to modify them inventively. Optionally, one might be able to write scripts to analyse her data.

Learning outcome, competences

knowledge:

• Technical: spreadsheet
• Conceptual: role of the descriptive statistics and its relation to the population statistics

attitude:

• More open to the explorative and conceptual analysis
• Statistics is understandable and can be used creatively

skills:

• Flexible data analysis with spreadsheet
• Finding new (and old but unused) methods

Content of the course

Topics of the course

• Advanced functions of spreadsheet software
  • Mathematical and statistical functions
  • Pivot tables and their limitations
  • Conditional formatting
  •  
• Statistical experimenting with spreadsheet software
• Conceptual background of BA statistics and alternative solutions
• Data analysis techniques various cognitive methods
  • reaction time, diffusion model
  • neuropsychology, single case statistics
  • developmental data
  • etc.

Learning activities, learning methods

Evaluation of outcomes

Learning requirements, mode of evaluation, criteria of evaluation:

requirements

• Data analysis methods
• Summarizing the methodological literature

mode of evaluation: practical – analysing own data or summarizing a less known method and its best practice

criteria of evaluation:

• New results
• Appropriate summary of the methodological litreture

Compulsory reading list

• None

Recommended reading list

• Spreadsheet tutorials and manuals
  • e.g., https://www.libreoffice.org/get-help/documentation/
• Data analysis and statistical tutorials
• Analysis libraries/modules for programming languages tutorials and manuals
  • e.g., http://docs.scipy.org/doc/