From the course: Introduction to jamovi
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Principal component analysis - jamovi Tutorial
From the course: Introduction to jamovi
Principal component analysis
- [Instructor] When you have a novel data set either because you created your own questions and got your own data or you're combining things that you don't really know if they've been put together before, one of the big questions is how can you combine things or what is the emergent structure of the data that you have. One of the most common ways of assessing this is with something called a principal component analysis. There's also the very closely related exploratory factor analysis, which we'll cover in another video. Principal component analysis works on the principle of covariance, which is closely related to correlation. Right now, we've got a data set here that is on the big five personality factors. It's included in the data that you downloaded from datalab.cc, and it addresses extroversion and openness and conscientiousness and so on. And, the question is how well do they go together and what is the structure that shows up empirically in the data. We know how they're supposed…
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