Importance of the Normal Distribution Curve and Its Application in Psychology

¶ … Normal Distribution Curve and Its Application in Psychology When a curve (reflecting the statistical results of the sampled population) is not skewed in any particular direction but is rather symmetrical (rather than being 'asymmetrical'). We have what is known as a "bell curve' or a Gaussian or a normal distribution. Not all symmetrical curves are normal, but all normal curves are symmetrical.

This specific type of curve is important in statistics since it has certain mathematical properties that can unilaterally be applied to a varying degree of situations all of which share the same characteristic of being bell-shaped (or of being normal distributions) in proportion. The normal distribution contains six standard deviations (three on each side of the mean).

The normal distribution is also the most straightforward of all and, therefore, the easiest in a way to compute particularly in terms of relationships of the mean, median, and mode to each toehr since all three central tendency measures occur at the same point (i.e. At the highest point of the curve in the center of the distribution). The total area underneath the curve and lying within the normal distribution is equal to one (1.0).

One refers to the fact that there is a 100% certainty that all scores, or values, for the "normally" distributed variable under study falls within the normal distribution. Parts of this 100% fall below the mean, and parts (e.g. another 50% will be after the mean, but all lie within the distribution. All scores are listed underneath the bell-curve. All points on either side of the mean have the same distance in equality to the mean.

For example, the distance of one standard deviation on the left of the mean is equal to the distance of one standard deviation to the right of the mean, making the area of the curve corresponding to these distances on either side of the mean identical. This equality is a constituent of the normal curve and something that makes it helpful to psychology in that different measurements can be based on the normal curve and applied to varying situations.

The Z score, for instance, are raw scores that are converted to units of standard deviation. These, because of the nature of the normal distribution, can be converted to percentiles or to other scores of measurement if necessary. The normal distribution is the shape that happens to occur the most often in describing a population, and it is lucky that it does because it can be precisely quantified by mathematical equations.

IQ scores are an ideal example of a normal distribution where you have the greatest frequency (or mean) in the middle with frequencies tapering off on either side. Because it occurs often and because the shape is mathematically guaranteed, parametric (i.e. those based upon a normal distribution) studies and statistical tools are.