The graphs in the new reports show a candidate’s score when compared with the general population and also when compared with the candidates in the overlay industry or demographic.

Both scores are presented as percentile scores. A percentile score is a score below which a certain percentage of the observations fall. So, for example, the 20th percentile is the value (or score) below which 20 percent of the observations may be found. In other words, if the candidate scores at the 20th percentile that means she scored higher than 20 percent of the population or, alternatively, 80 percent of the population scored higher than she did.

In this example, the candidate’s score () is at the 55th percentile against the general population. This means his score is higher than 55% of the population or, in other words, slightly higher than average.

The candidate scores at the 40th percentile () when compared with the population of candidates who represent to the overlaid industry or demographic. This means the candidate’s score is higher than 40% of that group or, conversely, lower than 60% of those candidates.

It is very important to remember the scores are **not** scores out of a
hundred but an indication of how the candidate ranks against the
particular population to which he or she is being compared. It is also
essential to understand that a higher score is not necessarily a
*better* score and a lower score is not necessarily a *worse*
score—it all depends on the particular trait as to how you
interpret your candidate’s scores.

Compare your candidates with industry and other demographic norms as well as the general population.