Quartiles Q1, Q2, Q3 of the series of distributing class intervals - calculator
Quartiles Q1, Q2, Q3 of the interval series
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Quartiles information
Quartile is one of the measures of central tendency used to determine the value of the feature around which the data is grouped. Therefore, it is about concentrating most of the data around some representative of the examined feature.
In the group of positional measures (measures of central tendency) quantiles can be distinguished, among which the most frequently used measures are quartiles (quarter values).
First (lower) quartile Q1 divides the group ordered into two parts in such a way that 25% of the units have a value not greater than Q1 , and the remaining 75% equal or greater than this quartile;
Formula for the estimate of the first quartile:
$$Q_1=x_{0Q1} + (N_{Q_1} - n_{isk-1}) · \frac{h_{Q_1}}{n_{Q_1}}$$
nQ1 - frequency of the first quartile (lower quartile)
x0Q1 - lower class boundary of the range containing the first quartile
nisk-1 - cumulative frequency range before the cumulative frequency of the first quartile
hQ1 = x1Q1(higher) - x0Q1(lower) - size (width) of the range containing the first quartile
NQ1 = \(\frac{n}{4}\) - first quartile number (position) for even observations
NQ1 = \(\frac{n+1}{4}\) - first quartile number (position) for odd observations
Second (middle) quartile Q 2 (median, middle value) divides the ordered group into two parts in such a way that half of the group's units have values of the variable equal to or greater than the median hence the median is sometimes called the middle value.
Formula for the estimate of the second quartile:
$$Q_2=x_{0Q2} + (N_{Q_2} - n_{isk-1}) · \frac{h_{Q_2}}{n_{Q_2}}$$
nQ2 - frequency of the second quartile (middle quartile)
x0Q2 - lower class boundary of the range containing the second quartile
nisk-1 - cumulative frequency range before the cumulative frequency of the second quartile
hQ2 = x1Q2(higher) - x0Q2(lower) - size (width) of the range containing the second quartile
NQ2 = \(\frac{n}{2}\) - second quartile number (position) for even observations
NQ2 = \(\frac{n+1}{2}\) - second quartile number (position) for odd observations
The third (upper) quartile Q3 divides the ordered group in such a way that 75% of units have feature values not higher than Q3 and the remaining 25 % not lower than Q3 .
Formula for the estimate of the third quartile:
$$Q_3=x_{0Q3} + (N_{Q_3} - n_{isk-1}) · \frac{h_{Q_3}}{n_{Q_3}}$$
nQ3 - frequency of the third quartile (upper quartile)
x0Q3 - lower class boundary of the range containing the third quartile
nisk-1 - cumulative frequency range before the cumulative frequency of the third quartile
hQ3 = x1Q3(higher) - x0Q3(lower) - size (width) of the range containing the third quartile
NQ3 = \(\frac{3·n}{4}\) - third quartile number (position) for even observations
NQ3 = \(\frac{3·(n+1)}{2}\) - third quartile number (position) for odd observations
EXAMPLE
In one of the companies, the distance between the employees' place of residence and the workplace was examined, the data was as follows:
Distance of residence in km. \( (x_{0i}+x_{1i})\) Number of employees \((n_i) \)
0-5 5
5-10 25
10-15 30
15-20 55
20-25 30
25-30 20
30-35 15
The task is to calculate the quartiles of the given distribution series.
First, we should calculate the cumulative frequencies. In our example, we add the values from the Number of employees column one by one. The calculations are presented in the table below.
Distance of residence in km. \( (x_{0i}+x_{1i})\) Number of employees \((n_i) \) Cumulative frequency \((n_{isk})\)
0-5 5 0+5=5
5-10 25 5+25=30
10-15 30 30+30=60
15-20 55 60+55=115
20-25 30 115+30=145
25-30 20 145+20=165
30-35 15 165+15=180
Now we can proceed to the calculation of the position (number) of the quartiles Q1 ,Q2 ,Q3 .
Position Q1 \(N_{Q_1}=\frac{n}{4}\)
Position Q2 \(N_{Q_2}=\frac{n}{2}\)
Position Q3 \(N_{Q_3}=\frac{3·n}{4}\)
where n this is the size of surveyed population. In our example, it is the number of all employees, n = 180, i.e. even (that's why we used the formula for even observations). Substituting to the formulas we get: $$N_{Q1}=\frac{180}{4}=45$$
$$N_{Q2}=\frac{180}{2}=90$$
$$N_{Q3}=\frac{3·180}{4}=135$$
To check what interval the quartiles belong to, look in the cumulative frequencies column for the first value greater or equal to the quartile position. This will be our task:
- for the first quartile Q1 the value is 60 . Because 60 is the first cumulative frequency greater than the number (position) of the 1st quartile - 45 . So we can see that Q1 belongs to the range 10-15 km , whose number (number of employees) is 30 .
- for the second quartile Q2 the value is 115 . Because 115 is the first cumulative frequency greater than the number (position) of the second quartile - 90 . So we can see that Q2 belongs to the range 15-20 km , whose number (number of employees) is 55 .
- for the third quartile Q3 the value is 145 . Because 145 is the first cumulative frequency greater than the number (position) of the third quartile - 135 . So we can see that Q3 belongs to the range 20-35 km , whose number (number of employees) is 30 .
Now we know what interval each of the quartiles belongs to, but we do not know their exact value. To calculate the value of quartiles of the interval series, we will use the following formulas to which we can substitute the data.
Quartile Q1
$$Q_1=x_{0Q1} + (N_{Q_1} - n_{isk-1}) · \frac{h_{Q_1}}{n_{Q_1}}$$
where:
x0Q1 = 10 - lower class boundary of the range containing the first quartile. Earlier, we established that this interval is 10-15 km, i.e. its lower limit will be 10.
NQ1 = 45 - position (number) of the first quartile, which we calculated earlier from the formula \( N_{Q1}=\frac{n}{4} \)
nisk-1 = 30 - cumulative frequency of the range that precedes the cumulative frequency to which the first quartile belongs. We determined that the cumulative frequency to which the first quartile belongs is 60. Looking at the row above in the table, we can see that the preceding cumulative number is 30.
hQ1 = x1Q1(higher) - x0Q1(lower) = 15-10 = 5 - size (width) of the range containing the first quartile. As we already know, the range of the first quartile is 10-15 km, so to calculate the width from the upper value, we subtract the lower value.
nQ1 = 30 - frequency of the range (number of employees) containing the first quartile.
Substituting into the formula for the first quartile we get: $$Q_1=10 + (45 - 30) · \frac{5}{30} = 12,5 $$
Quartile Q2
$$Q_2=x_{0Q2} + (N_{Q_2} - n_{isk-1}) · \frac{h_{Q_2}}{n_{Q_2}}$$
gdzie:
x0Q2 = 15 - lower class boundary of the range containing the second quartile. Earlier, we established that this interval is 15-20 km, i.e. its lower limit will be 15.
NQ2 = 90 - position (number) of the second quartile, which we calculated earlier from the formula \( N_{Q2}=\frac{n}{2} \)
nisk-1 = 60 - cumulative frequency of the range that precedes the cumulative frequency to which the second quartile belongs. We determined that the cumulative frequency to which the second quartile belongs is 115. Looking at the row above in the table, we can see that the preceding cumulative number is 60.
hQ2 = x1Q2(higher) - x0Q2(lower) = 20-15 = 5 - size (width) of the range containing the second quartile. As we already know, the range of the second quartile is 15-20 km, so to calculate the width from the upper value, we subtract the lower value.
nQ2 = 55 - frequency of the range (number of employees) containing the second quartile.
Substituting into the formula for the second quartile we get: $$Q_2=15 + (90 - 60) · \frac{5}{55} = 17,73 $$
Quartile Q3
$$Q_3=x_{0Q3} + (N_{Q_3} - n_{isk-1}) · \frac{h_{Q_3}}{n_{Q_3}}$$
gdzie:
x0Q3 = 20 - lower class boundary of the range containing the third quartile. Earlier, we established that this interval is 20-25 km, i.e. its lower limit will be 20.
NQ3 = 135 - position (number) of the third quartile, which we calculated earlier from the formula \( N_{Q3}=\frac{3·n}{2} \)
nisk-1 = 115 - cumulative frequency of the range that precedes the cumulative frequency to which the third quartile belongs. We determined that the cumulative frequency to which the third quartile belongs is 145. Looking at the row above in the table, we can see that the preceding cumulative number is 115.
hQ3 = x1Q3(higher) - x0Q3(lower) = 25-20 = 5 - size (width) of the range containing the third quartile. As we already know, the range of the third quartile is 20-25 km, so to calculate the width from the upper value, we subtract the lower value.
nQ3 = 30 - frequency of the range (number of employees) containing the third quartile.
Substituting into the formula for the third quartile we get: $$Q_3=20 + (135 - 115) · \frac{5}{30} = 23,33 $$
Interpretation: 25% of employees live within 12.5 km of their workplace and the remaining 75% live within 12.5 km of their workplace. And half of the employees live within 17.73 km or less and the other part more than 17.73 km from the workplace. We also calculated that the majority or 75% of workers live closer than 23.33 km from the workplace and the remaining 25% more.
Users of this calculator also used Percentile, Centile - calculator with explanation With the percentile calculator you will calculate the percentile position and find the value. Percentile or centile is a measure in statistics that indicates a value for which P Percentage of the Population is equal to or less than that value and 100-P is greater.
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