Central Currency

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Recommended: Application of Central tendency

Measures of central tendency which include, the mean, median and mode, attempt to provide the centre point of the data set as wells as represent it with all with one value. Whereas measures of variability (range, interquartile range, variance and standard deviation) attempt to show the spread or difference in a data set. The mean, also known as the average, is the sum of all the values in a set of data divided by the number of values in said set. For example a class of 10 students were administered an IQ test. The scores of which are as followed; 120, 120, 115, 127, 100, 140, 75, 110, 70, 104. In this case that number is 107.4, what this tells us is that the average score on the IQ test was 107.4. Unfortunately this value includes the outliers which can skew the distribution. If we were to put these scores in order from lowest to highest (70, 75, 100, 104, 110, 115, 120, 120, 120, 140) the score that is in the middle or the median would be 112.5. The median, unlike the mean, is not affected by the outliers, these are the scores or values that differ largely from the majority of the data set. In this case they are 70, 75, 140. The last measure of central tenancy is the mode, the most frequently occurring score or value in a data set, the mode being 120 in the current example. …show more content…

This means that they show the distribution of the values in the data set in relation to the mean. If the distribution or spread of the values is large then the mean is not representative of the set of data. If the data is distributed closely around the mean or shows little variability then the mean can be seen as representative of the data set. Also in order to compute the standard deviation the mean, median and mode must all be

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