Quartiles - another way to describe data

The only real alternative to the mean and SD as descriptors for sets of measurements is the system of quartiles . This enjoys a certain vogue in some research areas, but there are others where you will almost never see it used. We have already seen that the median is a value chosen to cut a set of data into two equal sized groups. Quartiles are an extension of that idea. Three quartiles are chosen so as to cut a data set into four equal-sized groups. 

The elimination half-lives of two synthetic steroids have been determined using two groups, each containing 15 volunteers. The results are shown in Table 2.5, with the values ranked from lowest to highest for each steroid. 

Look at steroid number 1 first. Among the ranked half-lives, we highlight the half-lives that are ranked as fourth, eighth and twelfth and these will provide the three quartile values. We have now chopped the set of data into four equal-sized groups. There are three half-lives shorter than Ql, three between Q1 and Q2, three between Q2 and Q3 and three above Q3. We then check back for the actual values of the three highlighted cases and they are found to be  

Rank Half-life (h) Rank Half-life (h) 

The second quartile (median) as an indicator of central tendency The second quartile has half the observations above it and half below and is therefore synonymous with the median. We have already established that the median is a useful and robust indicator of central tendency, especially when there are some extreme 

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