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Arrange the data in increasing order and count the number of data points = N. Find the integer K = N/2 or (N+1)/2. The Kth number in the ordered set is the median. Now consider only the numbers from the smallest to the median and find the median of this subset. This is the lower quartile = Q1. Then consider only the numbers from the original median to the largest. Find the median of this subset. It is the upper quartile = Q3. Then IQR = Q3 - Q1
There is no formal definition of a outlier: it is a data point that is way out of line wit the remaining data set.If Q1 and Q3 are the lower and upper quartiles of the data set, then (Q3 - Q1) is the inter quartile range IQR. A high end outlier is determined by a value which is larger thanQ3 + k*IQR for some positive value k. k = 1.5 is sometimes used.
The mean of a set of data is the sum of that data divided by the number of items of data.
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procedure: step 1: arrange your raw data in increasing order. step 2: find the Q1 is the size of the (n+1)/4th value. step 3: find the Q3 is the size of the 3(n+1)/4th value. Quartile Deviation(QD)= (Q3-Q1)/2 for example: 87 ,64,74,13,19,27,60,51,53,29,47 is the given data step 1: 13,19,27,29,47,51,53,60,64,74,87 step 2: (n+1)/4=3 therefore Q1=27 step 3: 3(n+1)/4=9 therefore Q3=6 implies QD=18.5