terms/normalcurve.txt · Last modified: 13 May, 2019 @ 11:44am by Jan Viljoen | Approved (version: 1)

Normal Distribution Curve

The key focus of AltanaESP assessments is to provide individuals with relevant and “related to..” feedbacks which might result in more refined orientations. The Normal Distribution or Bell Curve is one of the many possible reference tools that a facilitator/coach can use to guide an individual to gain a more reliable personal orientation (i.e. accurate PVC) for the dynamic system in which s/he operates and functions.

In both probability theories (e.g. assessment reports) and statistics (scored assessment instruments) the normal distribution curve can be regarded as a continuous probability distribution (sourcing from evolving norms tables) that describes the data (i.e. results) that cluster around the mean. The graph of the associated probability density function is bell-shaped, with a peak at the mean. The normal distribution curve can be used to describe - at least approximately - any variable that tends to cluster around the mean. For example, the heights of adult males in South Africa are normally (i.e. on average) distributed, with a mean of about 1.8 meters. Most men have a height close to the mean, though a small number of men have a height significantly either above or below the mean.

Thus, the sum of a large number of “independent random variables” are distributed normally. For this reason, the normal distribution curve is frequently used throughout statistics, natural science and social science as a simple reference model for more complex phenomena. The normal distribution curve in AltanaESP assessments is primarily deployed to reference an individual's estimated level of performance in relation to the performance levels of other people. The foundation of the normal distribution probability curve is is based on the dimensions of human beingness and different data filters that can be used to create a more appropriate “picture” of performance levels from different angles or assessment dimensions.

For example…

An individual completes an archetype questionnaire to highlight certain characteristics or personality dimensions. Feedback can be given using “difference dimension” data filters applying the normal distribution curve to “compare” assessment results with suchlike assessments previously completed by the individual (i.e. cumulative assessments). For a “bigger-picture” feedback , “similar contextual” data filters - normal distribution curve based - can be used to indicate an estimated “distribution reference” as it relates to age, gender, level of schooling, family milieu, job environments, …etc. Additionally feedbacks can also be done using “sameness dimension” data filters to “compare” individual results with the results of all the persons that completed the specific questionnaire.

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  • Last modified: 13 May, 2019 @ 11:44am
  • by Jan Viljoen