Introduction to study design and statistics - 2025 Fall

Dates Thursday, 5:15-6:45 pm

Venue Izu 116

Aims The aim of the course is to learn the basics of study design and mathematical statistics. By the end of the semester, you should be able to understand and run simple statistical analyses common in cognitive science and understand the related study design. The course will also provide a firm background to learn additional topics after the semester.

You can bring your computer to the class.

The course is for Cognitive Science MSc students who haven't learn the statistics topics listed below. Contact me if you're interested in the course, but you have another major.

Topics

More links and slides will be added during the semester.

• Bases of study design and statistics

  • Introduction to methodology (slides)

  • Introduction to statistics (slides)

• Planning a data collection

  • Google Form use (brief info, help)

• More bases of statistics

  • Measurement levels (slides)

  • Sample and population (slides, spreadsheet demonstration)

• Software solutions

  • Software packages for data analysis and statistics (slides)

  • Using spreadsheet (slides)

    • Data file for practice

  • Using CogStat (general slides, short slideshow about use, and extra slides about the recent features)

  • Using jamovi (user guide, getting started, and community resources)

  • Statistical software packages: data arrangement, variables, and their properties, data exchange between packages (slides)

• Simple descriptive statistics for a single variable (slides, additional and optional (currently Hungarian) slides)

• Statistical hypothesis test (slides about the general ideas, (currently Hungarian) slides about choosing the right test)

  • Studying a single sample distribution

    • Data file for practice

• Describing variable pairs (slides TBA, CS slides TBA)

  • Linear fit

• Comparing conditions and groups (slides TBA, CS slides TBA)

  • Comparing two conditions or groups

  • Comparing more than two conditions or groups

  • Multi-way comparison

• Studying nominal variables (slides TBA)

  • Comparing nominal variables

  • Relation of nominal variables

• Presenting the results (slides TBA)

  • Making diagrams

  • Presenting in text

Data collection materials

TBD

Requirements

• Class attendance (minimum requirement: not more than 3 missed classes)

• Homeworks ( minimum requirement: not more than 2 missed homeworks)

• Midterm and final exams

The grade will be the mean of the two exam grades, provided that class attendance and homework requirements are met.

Recommended software packages

• LibreOffice

• CogStat

• jamovi