![]() Where \(n\) is the sample size, and \(k\) is the corresponding order of the quartile (\(k\) = 1, 2 or 3). Of the k-th quartile \(Q_k\) is computed using the formula: In order to do so, the sample data is first organized in ascending order. In the case of sample data, which means that you DON'T HAVE all the values of the population, you only have a sample, the quartiles can be only estimated. The k-th quartile (first, second or third quartile) of a distribution corresponds to a point with the property that 25% of the distribution is to the left of the first quartile (\(Q_1\)), 50% of the distribution is to the left of the second quartile (\(Q_2\)) and 75% of the distribution is to the left of the third quartile (\(Q_3\))
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