![]() Given other traits on which I am measured, I might not be the best fit for the sales person and there there may be a candidate whose personality perferences make him more likely to perform well in that situation. ![]() I may find that quite a challenging function of my work, as opposed to the person who enjoys alot of personal interaction and has little difficulty in meeting strangers. Lets say I score very low on extroversion and I am being recruited for as a sales person who has to meet new people all the time and in new or unfamiliar situations. ![]() How might this be valuable in recruitment? Here is a hypothetical case. The results for the individual are COMPARED against the norm group for how he/she scored in that comparision.įor example, if a candidate is rated high on extroversion on a norm referenced test, then that person is likely to be more inclined to prefer alot of personal interaction as opposed to someone whose focus may be more task oriented. Now you have the basis upon which to compare a current test taker on a particular scale of the test, say extroversion, again the norms for his/her peer group. Stats like mean, mode, standard deviation, ( and a few more) are used to come with the norms for the said group. What that means is the test has been adminstered to large enough sample of a group, ie, Emiraiti Nationals, or UAE Expats, or First language French, etc, to obtain a data that can be analyzed with statistical tools, to obtain a frequency distribution, or what is often called the "bell curve" I will attempt a simple, high level explanation of how norm referenced are created and used. The term "normative assessment" refers to the process of comparing one test-taker to his or her peers. ![]() This estimate is derived from the analysis of test scores and possibly other relevant data from a sample drawn from the population. A norm-referenced test / NRT is a type of test, assessment, or evaluation which yields an estimate of the position of the tested individual in a predefined population, with respect to the trait being measured. ![]()
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