Further, using raw scores, we cannot identify how a person has performed across a range of tests or questionnaires unless we can get a standard which can be applied to all the tests. Using norms to evaluate performance, we may find that somebody performs strongly using language skills, but is relatively weak in computational skills. Norms therefore provide a frame of reference with which to view a candidate's performance.

Norms are constructed from a set of scores of candidates that are representative of the population you are measuring or comparing against. A candidate's scores can then be directly compared with the norm group, and the relative performance of the candidate can be identified by how the candidate falls in the distribution of scores on the norm table. In this way one can tell whether a candidate is anything from very poor or low, to average, to exceptional on an ability or characteristic.

Lets have a look at some examples of how norms can be used:

i. When assessing a bursary candidate for his or her suitability for university, it is useful to know how the person compares against students who have been successful at that level. By comparing the performance of the candidate on a number of psychometric tests against the norm group of successful students, you can evaluate the likely success of the candidate in obtaining the qualification.

ii. In a selection exercise within an organisation you want an overall profile of how good the candidates are on a range of measures. These may include psychometric tests and questionnaires. Use of a norm table composed of all internal personnel provides a profile of the performance of all candidates on the same criteria, and shows the relative strengths and weaknesses of individuals as well as how they compare to the standard in the company.

iii. As part of a development scheme for personnel, a company may offer an assertiveness course. Candidates complete a questionnaire on assertiveness and compare their scores with those of a norm composed of a representative sample of the general population. They can then see exactly how assertive they are relative to the next person.

iv. Use is made of an imported questionnaire as part of an organisation's management training program. The questionnaire measures conflict styles. Using norms generated from the scores of South African managers, the trainees can compare their own profiles with the norm and begin to adapt their behaviour where necessary.

Measurements taken on large groups of people will generally create a distribution which takes the approximate form of a normal bell shaped curve. For example, if we have a look at the shoe size of the adult male population, it will fall in a range of scores from very small to very large, with the majority of people somewhere in the middle.  

The normal curve is characterised by a concentration of observations in the middle and as the distance from the central point increases on either side, the incidence of people is reduced. By plotting the distribution above, we can see where any particular shoe size will be located on the normal distribution. These distributions also exist for other measures such as height, weight, and even blood pressure. Similar principles can be established for psychometric tests and questionnaires which are measuring a particular ability or trait. Using the information of a distribution we can make assessments and even predictions about outcomes. For instance, shoe makers will cater for the central tendency of sizes by making a large number of shoes between sizes seven and nine. Few shoes will be made smaller and larger than this, because the market is relatively smaller. In the case of psychometric measurements, we can locate a person's performance on the distribution curve and it will tell us whether he or she scored very well, average, or low on the quality relative to the distribution of the sample.

Norms therefore provide the following benefits:

Tests and other instruments vary in difficulty and they seldom consist of the same number of items. Norms overcome these difficulties by providing a standardised way of viewing performance. No matter how tests may vary in length or difficulty, we can compare the person's performance against a common standard using norms. Further, we may want to compare people to a variety of different groups. So, for example, we can have a range of norms for a test varying from matriculants, through Technicon graduates, to University graduates. We can also develop norms for cultural groups where we know the instruments we are using are influenced by cultural factors. Separate norms may provide an unbiased way of assessing people on the same instrument and compensating for cultural bias in the instrument.

 The process utilised in NormMaker smooths and normalises the distribution of a set of scores to provide a norm table. The norm table can then be used to locate the raw score, and identify where the person falls in the distribution. The norm tables that are produced by NormMaker provide three ways in which we can view the distribution. These are: