When you’re working with many correlated variables, they get too unwieldy to use individually.
Principal component analysis allows you to combine these variables while extracting the most possible information they contain. It’s an important variable reduction technique.
And it’s not as simple as averaging them. You lose a lot with a simple approach like that.
In this training, you’ll learn what principal component analysis does, key concepts and terminology (eigenvalues, anyone?), the steps to take and the important decisions on each step.
Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.
About the Instructor
Karen Grace-Martin helps statistics practitioners gain an intuitive understanding of how statistics is applied to real data in research studies.
She has guided and trained researchers through their statistical analysis for over 15 years as a statistical consultant at Cornell University and through The Analysis Factor. She has master’s degrees in both applied statistics and social psychology and is an expert in SPSS and SAS.
Just head over and sign up for Statistically Speaking. You'll get access to this training webinar, 130+ other stats trainings, a pathway to work through the trainings that you need — plus the expert guidance you need to build statistical skill with live Q&A sessions and an ask-a-mentor forum.
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