Anmeldung: Statistik II – Factor Analysis and Principal Component Analysis [ENG]

Many phenomena in everyday life, as well in science, are influenced by factors that cannot be measured directly. For instance, the personality trait “openness” cannot be objectively assessed by one single measure. Yet, it might influence a variety of other, directly measurable variables, such as “profession”, “favorite music style” or “frequency of restaurant visits”. Factor Analysis (FA) and Principal Component Analysis (PCA) aim at revealing and quantifying this kind of underlying factors. At the same time, they allow to reduce data in both, their amount and complexity. For this reason, FA and PCA are among the most important tools for generating and testing hypotheses, for developing questionnaires and for data compression. In this course participants learn how to utilize these versatile tools for their own research. Exercises in the free statistics software Jamovi illustrate the theoretical concepts and enable the participants to put them into practice. To optimally benefit from the course, participants should be familiar with basic statistical concepts and linear regression in particular.

Inhalt und Lernziele

• Understanding the theoretical foundations of factor and principal component analyses
• Confident handling of practical aspects and possible problems during implementation
• Confident application of the method in everyday research