If need do the problem in R. If used Submit both R code and the solution.
Problem: The data given in the file ‘ESR_data.csv’
are 5-point Likert items taken from the Experiences in Close Relationships Scale web-based
personality assessment. Techniques, such as Principal Component Analysis (PCA), can be used to
determine different types of personalities. There are 51,491 subjects in the file and 36 variable items
as follows:
A) How many components are need to explain 100% of total variation for this data? How many
components are determined from the scree plot? What number of components would you use
in the model?
B) For the number of components in part A, give the formula for each component and a brief
interpretation after rotating the components. What names might you give for each of the
components?
C) What subjects have the highest and lowest values for each principal component (only include
the number of components specified in part A. For each of those subjects, give the principal
component scores (again only for the number of components specified in part A).
D) Finally, run a common factor analysis on the same data. What difference, if any, do you find?
Does the factor analysis change your ability to interpret the results practically?
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