Quartiles

Introduction to Quantiles and Quartiles

Quantiles are the techniques used to divide the data into different equal parts. For example, quantiles divide the data into four equal parts. Quartile comes from quarter which means 4th part. Deciles divide the data into ten equal parts and they come from deca means the 10th part. Percentiles divide the data into hundred parts and it comes to percent which means the 100th part.

Therefore, quartiles, deciles, and percentiles are used to divide the data into 4, 10, and 100 parts respectively. The quantiles, deciles, and percentiles are collectively called quantiles.

Quartiles are the rules which divide the data into four equal parts. When we divide any data into four equal parts then we cut it at e equidistant points. Therequartiles ($Q_1, Q_2$, and $Q_3$) as quartiles divide the data into four equal parts so divide the number of observations by four for each quartile.

Quartiles for Ungroup Data

\begin{align*}
Q_1 &= \left(\frac{n+1}{4}\right)th \text{ value is the} \frac{1}{4} \text{ part}\\
Q_2 &= \left(\frac{2(n+1)}{4}\right)th \text{ value is the} \frac{2}{4} \text{ part}\\
\left(\frac{3(n+1)}{4}\right)th \text{ value is the} \frac{3}{4} \text{ part}
\end{align*}

The following ungroup data has 96 observations $(n=96)$

22	22	25	25	30	30	30	31	31	33	36	39
40	40	42	42	48	48	50	51	52	55	57	59
81	86	89	89	90	91	91	91	92	93	93	93
93	94	94	94	95	96	96	96	97	97	98	98
99	99	99	100	100	100	101	101	102	102	102	102
102	103	103	104	104	104	105	106	106	106	107	108
108	108	109	109	109	110	111	112	112	113	113	113
113	114	115	116	116	117	117	117	118	118	119	121

The first, second, and third quartiles of the above data set are:

\begin{align*}
Q_1 &= \left(\frac{n}{4}\right)th \text{ position } = \left(\frac{96}{4} = 24th \text{ value} = 59\\
Q_2 &= \left(\frac{2\times 96}{4}\right) = 48th \text{position} = 98\\
Q_3 &= \left(\frac{3\times n}{4}\right)th = \left(\frac{3\times 96}{}\right)th \text{ position} = 72th \text{ position} = 108
\end{align*}

Note that the above data is already sorted. If data is not sorted, first we need to arrange/sort the data in ascending order.

Quartiles for Gruoped Data

For the following grouped data one can also compute the quantiles, hence the quartiles.

Classes	f	x	C.B.	CF
65-84	9	74.5	64.5-84.5	9
85-104	10	94.5	84.5-104.5	19
105-124	17	114.5	104.4.5-124.5	36
125-144	10	134.5	124.5-144.5	46
145-164	5	154.5	144.5-164.5	51
165-184	4	174.5	164.5-184.4	55
185-204	5	194.5	184.5-204.5	60
Total	60

From the above-grouped data, we have 60 observations $(n=60)= \sum\limits_{i=1}^n = f_i = \Sigma f = 60$. The three quartile will be

\begin{align*}
\frac{n}{4} &= \left(\frac{60}{4}\right)th = 15th \text{ value}\\
Q_1 &= l + \frac{h}{f}\left(\frac{n}{4} – CF\right) = 84.5 + \frac{20}{10}(15-9) = 96.5\\
\frac{2n}{4} &= \left(\frac{2\times 60}{4} \right) = 30th \text{ value}\\
Q_2 &= l + \frac{h}{f}\left(\frac{2n}{4} – CF\right) = 104.5 + \frac{20}{17}(30-19) = 117.44\\
\frac{3n}{4} &= \left(\frac{3\times 60}{4} \right) = 45th \text{ value}\\
Q_3 &= l + \frac{h}{f}\left(\frac{3n}{4} – CF\right) = 124.5 + \frac{20}{17}(45-36) = 142.5\\
\end{align*}

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