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<br />. <br /> <br />. <br /> <br />Descriptive statistics are then generated to descr',be question frequency charac- <br />teristics. The normal distribution in statistics can be defined in terms of mo- <br />ments. These moments are computed by a frequency function and determine <br />distance away from an arbitrary point, usually the mean, in the normal distrib- <br />ution curve. Therefore, moments describe characteristics of the normal distrib- <br />ution in mathematical terms. The mean of the curve is the first moment and it <br />is convenient to use it to calculate the higher moments, The second moment is <br />a measure of the dispersion of data around the mean and is called standard de- <br />viation. The third moment is a measure of the deviation from symmetry of the <br />curve about the mean and is termed skewness. Skewness is a measure of devi- <br />ation of data from a normal distribution. A positive skewness value indicates an <br />excess of distribution of data points to the right of the mean and negative <br />skewness is a excess of data to the left of the mean. The value for skewness <br />in a normal distribution is zero. The fourth moment is a measure of the <br />peakedness, or kurtosis of the distribution curve. This kurtosis moment provides <br />a measure of the grouping of data points in relation to normal distribution. If <br />there are an excess of points around the mean, the distribution curve will have <br />a sharp central peak. A frequency distribution is generally considered normal <br />if its skewness is 0 and its kurtosis is 3. <br /> <br />Data presentation will be in tabular and graphical forms. Assessment of these <br />data outputs will make it possible to quantify user perceptions and opinions. <br /> <br />7 <br />