Briefly discuss how norms are used to compare raw scores of individuals.

Question

What will be an ideal response?

Answer 1

We need a more precise way of expressing each individual’s position relative to the norm group. This is accomplished easily by converting raw scores into some relative measure--usually percentile ranks or standard scores. The percentile rank of a given raw score refers to the percentage of persons in the norm group who fall below it. Standard scores may be expressed either as z scores (i.e., the distance of each raw score from the mean in standard deviation units) or as some modification of the z score that eliminates negative numbers and decimal notation. A hypothetical norm table may be used. The baseline is presented in a generalized form, marked off in standard deviation units. For example, if the mean of a distribution of scores is 30 and if the standard deviation is 8, then ±1s corresponds to 38 (30 +8) and 22 (30 – 8), respectively. Also, since the total area under the curve represents the total distribution of scores, we can mark off subareas of the total corresponding to ±1, 2, 3, and 4 standard deviations. The numbers in these subareas are percentages of the total number of people. Thus, in a normal distribution of scores, roughly two-thirds (68.26 percent) of all cases lie between ±1 standard deviation. This same area also includes scores that lie above the 16th percentile and below the 84th percentile.