Why career interest results use averages instead of raw totals

If one interest group has more questions than another, its raw total has more opportunities to grow. Comparing averages prevents that difference in item counts from deciding the ranking by itself.

Work through the arithmetic

Imagine group A contains 10 questions and your scoring values add up to 40. Its mean is 40 divided by 10, or 4. Imagine group B contains 14 questions and your values add up to 49. Its mean is 49 divided by 14, or 3.5.

Group B has the larger raw total, but group A has the larger average response. On PickAQuiz's 0–100 response display, their positions would be 75 and 62.5 before display rounding. The positions describe your answers on the scale, not percentages of people or probabilities of career success.

What is included in the ORVIS profile

The complete inventory has 92 items organised into eight dimensions. The source key assigns the items to those dimensions. Our implementation keeps the inventory complete, counts each group's answers and computes a mean for that group.

We do not weight a group more heavily because it appears more prestigious or because a particular occupation pays more. We also do not combine the dimensions into an overall career score. Interest in different activities is the subject of the profile.

What this calculation cannot establish

Averaging fixes the simple item-count problem. It does not make every small difference meaningful, remove uncertainty in self-reporting or establish how you compare with a population. Scores also depend on understanding the activity descriptions and using the response scale consistently.

When reviewing a result, inspect the activities that appealed to you, note any unfamiliar wording and select a few things to investigate. For the source assignments and published research reference, see the ORVIS scoring key. The percentage-style display is a PickAQuiz presentation choice.