1. Suppose you are conducting a survey and you want to know whether the items in the survey have similar patterns of responses, do these items “hang together” to create a construct? The basic assumption of factor analysis is that for a collection of observed variables, there are a set of underlying variables called factors (smaller than the observed variables), that can explain the interrelationships among those variables.

STEP 1
Get the correlation between the items of the quesitonnaire (32 x 32 matrix) in a table format with a right angle shade of correlations in one-half

2. From this table we can see that most items have some correlation with each other ranging from for Items 3 and 7 to for Items 6 and 7. Due to relatively high correlations among items, this would be a good candidate for factor analysis. Recall that the goal of factor analysis is to model the interrelationships between items with fewer (latent) variables. These interrelationships can be broken up into multiple components
STEP 2
ANY CORRELATION EQUAL TO OR ABOVE - 0.38 is acceptable as high correlation in the field of emotions