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Problem 4 ( Principal Component Analysis - 2 0 points ) : The data given in the file Big 5 . csv are 5 -
Problem Principal Component Analysis points:The data given in the file Bigcsv are point Likert items taken from the Big Five Personality Test webbased personality assessment. Techniques, such as Principal Component Analysis PCA can be used to determine different types of personalities. There are subjects in the file and variable items as follows:
E I am the life of the party.
E I don't talk a lot.
E I feel comfortable around people.
E I keep in the background.
E I start conversations.
E I have little to say.
E I talk to a lot of different people at parties.
E I don't like to draw attention to myself.
E I don't mind being the center of attention.
E I am quiet around strangers.
N I get stressed out easily.
N I am relaxed most of the time.
N I worry about things.
N I seldom feel blue.
N I am easily disturbed.
N I get upset easily.
N I change my mood a lot.
N I have frequent mood swings.
N I get irritated easily.
N I often feel blue.
A I feel little concern for others.
A I am interested in people.
A I insult people.
A I sympathize with others' feelings.
A I am not interested in other people's problems.
A I have a soft heart.
A I am not really interested in others.
A I take time out for others.
A I feel others' emotions.
A I make people feel at ease.
C I am always prepared.
C I leave my belongings around.
C I pay attention to details.
C I make a mess of things.
C I get chores done right away.
C I often forget to put things back in their proper place.
C I like order.
C I shirk my duties.
C I follow a schedule.
C I am exacting in my work.
O I have a rich vocabulary.
O I have difficulty understanding abstract ideas.
O I have a vivid imagination.
O I am not interested in abstract ideas.
O I have excellent ideas.
O I do not have a good imagination.
O I am quick to understand things.
O I use difficult words.
O I spend time reflecting on things.
O I am full of ideas.
AHow many components are need to explain 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?
AFor the number of components in part A give the formula for the first component and a brief interpretation after rotating the components. What names might you give for each of the components?
AWhat subjects' scores 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
AFinally, 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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