

The measures of partition in statistics are explained below
Median of a distribution divides it into two equal parts. It is also possible to divide it into more than two equal parts. The values that divide a distribution into more than two equal parts are commonly known as partition values or fractiles. Some important partition values are discussed in the following sections.
Quartiles
The values of a variable that divide a distribution into four equal parts are called quartiles. Since three values are needed to divide a distribution into four parts, there are three quartiles, viz. Q1, Q2 and Q3, known as the first, second and the third quartile respectively. For a discrete distribution, the first quartile (Q1) is defined as that value of the variate such that at least 25% of the observations are less than or equal to it and at least 75% of the observations are greater than or equal to it.
For a continuous or grouped frequency distribution, Q1 is that value of the variate such that the area under the histogram to the left of the ordinate at Q1 is 25% and the area to its right is 75%. The formula for the computation of Q1 can be written by making suitable changes in the formula of median.
After locating the first quartile class, the formula for Q1 can be written as follows:
Here, LQ1 is lower limit of the first quartile class, h is its width, fQ1 is its frequency and C is cumulative frequency of classes preceding the first quartile class.
By definition, the second quartile is median of the distribution. The third quartile (Q3) of a distribution can also be defined in a similar manner.
For a discrete distribution, Q3 is that value of the variate such that at least 75% of the observations are less than or equal to it and at least 25% of the observations are greater than or equal to it.
For a grouped frequency distribution, Q3 is that value of the variate such that area under the histogram to the left of the ordinate at Q3 is 75% and the area to its right is 25%. The formula for computation of Q3 can be written as
Deciles
Deciles divide a distribution into 10 equal parts and there are, in all, 9 deciles denoted as D1, D2, ...... D9 respectively.
For a discrete distribution, the i th decile Di is that value of the variate such that at least (10i)% of the observation are less than or equal to it and at least (100  10i)% of the observations are greater than or equal to it (i = 1, 2, ...... 9).
For a continuous or grouped frequency distribution, Di is that value of the variate such that the area under the histogram to the left of the ordinate at Di is (10i)% and the area to its right is (100  10i)%. The formula for the ith decile can be written as
Percentiles
Percentiles divide a distribution into 100 equal parts and there are, in all, 99 percentiles denoted as P1, P2, ...... P25, ...... P40, ...... P60, ...... P99 respectively.
For a discrete distribution, the kth percentile Pk is that value of the variate such that at least k% of the observations are less than or equal to it and at least (100  k)% of the observations are greater than or equal to it.
For a grouped frequency distribution, Pk is that value of the variate such that the area under the histogram to the left of the ordinate at Pk is k% and the area to its right is (100  k)% . The formula for the kth percentile can be written as
Remarks :
(i) We may note here that P25 = Q1, P50 = D5 = Q2 = Md, P75 = Q3, P10 = D1, P20 = D2, etc.
(ii) In continuation of the above, the partition values are known as Quintiles (Octiles) if a distribution is divided in to 5 (8) equal parts.
(iii) The formulae for various partition values of a grouped frequency distribution, given so far, are based on 'less than' type cumulative frequencies. The corresponding formulae based on 'greater than' type cumulative frequencies can be written in a similar manner, as given below:
Here UQ1 ,UQ3 ,UDi ,UPK are the upper limits of the corresponding classes and C denotes the greater than type cumulative frequencies.
Example: Locate Median, Q1, Q3, D4, D7, P15, P60 and P90 from the following data:
Solution: First we calculate the cumulative frequencies, as in the following table:
Example : Calculate median, quartiles, 3rd and 6th deciles and 40th and 70th percentiles, from the following data
Also determine (i) The percentage of workers getting weekly wages between Rs 125 and Rs 260 and (ii) percentage of worker getting wages greater than Rs 340.
Solution: First we make a cumulative frequency distribution table :
(i) Calculation of median: Here N = 500 so that
N/2= 250. Thus, median class is
250  300 and hence Lm = 250, fm = 125, h = 50 and C = 150.
Substituting these values in the formula for median, we get
Md = 250 + 250150/125x50 = Rs 290
Hint: The given percentage of walkers and cyclists can be taken as frequencies. For calculation of mean, the necessary assumption is that the width of the first class is equal to the width of the following class, i.e., 1/4. On this assumption, the lower limit of the first class can be taken as 0. Similarly, on the assumption that width of the last class is equal to the width of last but one class, the upper limit of last class can be taken as 6. No assumption is needed for the calculation of median.
Hint: Add 200, 150 and 150 to the respective frequencies of the class intervals
450  500, 550  600 and 650  700.
Draw 'less than' and 'more than' type ogives for the above data and answer the following from the graph:
(i) If the minimum marks required for passing are 35, what percentage of candidates pass the examination?
(ii) It is decided to allow 80% of the candidate to pass, what should be the minimum marks for passing?
(iii) Find the median of the distribution.
Hint: See example above.
In which subject the level of knowledge of student is higher?
Hint: Compare median of the two series.


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