A data scientist runs PROC FACTOR and examines the communality estimates in the output. What does a communality value of 0.25 for a variable named 'age' indicate?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because communality is the proportion of a variable's variance that is explained by the retained factors. A communality of 0.25 for 'age' means only 25% of age's variance is captured by the factor solution — age is poorly represented.
Full explanation below image
Full Explanation
B is correct because communality is the proportion of a variable's variance that is explained by the retained factors. A communality of 0.25 for 'age' means only 25% of age's variance is captured by the factor solution — age is poorly represented. A data scientist would either retain more factors, remove age from the analysis, or accept that age does not fit well in the factor structure. A confuses communality with contribution to total variance. C confuses communality with a factor loading. D confuses communality with a correlation coefficient.