**Percentile Score**

This is the most important score as it ranks where the candidate's score sits relative to the results achieved by people in the norm group (or 'comparison group'). Percentile scores are best explained through examples. If a candidate scores in the 50th percentile, this means that the candidate's score is higher than 50% of the scores achieved by people in the norm group. If a candidate scores in the 90th percentile, they have scored higher than 90% of the norm group, putting them in the top 10%. If a candidate scores in the 10th percentile, they have scored higher than 10% of the norm group, putting them in the bottom 10%.

A percentile score together with the norm group give context to your candidate's results. The alternative would be to just give a raw score of say, 14 out of 20. But that wouldn't tell you much without knowing what other people scored. Is 14/20 a good score, a bad score, or average? We don't know, unless we compare it with scores other people achieved. That's where a percentile score comes in handy.

**Sten Score**

This is an abbreviation of standard ten'. This is can be thought of as another way of expressing a percentile score, but on a scale of 1 to 10 instead of 1 to 100. Like percentiles, sten scores are not in a linear scale; they fit a normal distribution curve to represent the fact that most people's scores bunch around the average with very few people at the extremities.

**Z Score**

You don't really need to worry about this; the z-score is a measure psychologists use to calculate the percentile score. If you are performing statistical analyses on the scores you might want to know the z-score but for most people this is not useful.

We also have a more in-depth article on how to interpret reports HERE.

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