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Exploratory Factor Analysis

Exploratory Factor Analysis

Intelligence. Compassion. Depression. Determination. Anxiety. Leadership. These are examples of qualities, or factors, that are difficult to measure directly. But we may be able to infer their existence from quantities that we can measure such as survey questions or test scores. Exploratory Factor Analysis, or EFA, is the statistical method of exploring data for the possible of existence of such factors. In this workshop we introduce the basics of EFA and demonstrate how to perform an EFA using the R statistical programming environment. Prerequisites: basic understanding of correlation and covariance. Might also be helpful to know how to open a R script in RStudio and submit R code, though we’ll demonstrate that in the workshop.

Instructor: Clay Ford

Tuesday, February 6, 2018
10:00am - 12:00pm
Brown 133
Brown Science & Engineering
Data Workshop Workshop
Clay Ford
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Event Organizer

Clay Ford
Michele Claibourn

Thank you for registering for a Research Data Services worskhop!