Quantitative Data Analysis: Issues & Applications (2026 DSS)

About

Sound knowledge of quantitative analysis is an essential requirement in many disciplines – more than one would expect! This course seeks to equip students with a critical understanding of (a) key concepts of statistical inference (e.g., Type I and II error, statistical significance & NHST, effect size, statistical power) and (b) different methods of data analysis (e.g., analysis of (co)variance, linear and logistic regression modelling, PCA, factor analysis).
The course integrates analytical theory with practical examples in a logical and straightforward manner to guide students through different techniques of quantitative data analysis. As such, it is targeted to doctoral students who either feel they lack a solid analytical background or simply want to refresh and improve their analytical and statistical inference skills.

Course leader

Georgios HALKIAS, Copenhagen Business School, Denmark

Target group

The Doctoral Summer School online courses are aimed at doctoral students, post-docs, academics and professionals from different fields and from all over the world.

Course aim

After taking this course, students will be able to:
- Understand the logic and principles of quantitative data analysis.
- Improve statistical inference skills.
- Apply the appropriate analytical techniques to answer different research questions.
- Interpret and critically assess research results.
- Identify not-that-obvious information.
- Draw valid conclusions to improve decision-making.
- Familiarize themselves with the IBM SPSS and JAMOVI interface.

Fee info