In this sample, our object is to find which people are similar. The procedure could be used to find two similar samples for the research's experimental and control groups. Thus, if stastical differences were found, they could be attributed to the treatment and not to initial differences between groups. This is the data we will be working with doing hand clustering.
Standardization recasts the variables into dimensionless z-score units.
This is usually important in the social sciences. For now, we will work with the orignial data. There are many different resemblance coefficients to choose from. Euclidean distance uses the Pythagorean Theorem to find the distance between cases. There are many different algorithms for clustering resemblance matrices, but most incrementally eat away the resemblance matrix and develop a clustering tree or dendogram.