6,6,9,5,8,9,6,7,8,8,6,5,5,6,8,5,7,7,8,6,5,9,10,14,5,8,5,8,10,10,7,7,7,8,6,6,7,5,7,8,8,5,6,6,7,7,7,6,6,9
coefficient of quartile deviation: (Q3-Q1)/(Q3+Q1)
(q3-q1)/2
Interquartile deviation Qd=(q3-q1) / 2
first quartile (Q1) : Total number of term(N)/4 = Nth term third quartile (Q3): 3 x (N)/4th term
Stability factor is defined as the proportion of Q1 to Q3 (Quartile 1/ Quartile 3) and is a measure of the dispersion of the population. A SF of 1 is the most desirable. SF < 0.9 indicates control issues and SF > 0.9 indicates technology issues.
coefficient of quartile deviation: (Q3-Q1)/(Q3+Q1)
coefficient of quartile deviation is = (q3-q1)/(q3+q1)
Q3-q1
(q3-q1)/2
(q3-q1)/2
Step 1: Find the upper quartile, Q3.Step 2: Find the lower quartile: Q1.Step 3: Calculate IQR = Q3 - Q1.Step 1: Find the upper quartile, Q3.Step 2: Find the lower quartile: Q1.Step 3: Calculate IQR = Q3 - Q1.Step 1: Find the upper quartile, Q3.Step 2: Find the lower quartile: Q1.Step 3: Calculate IQR = Q3 - Q1.Step 1: Find the upper quartile, Q3.Step 2: Find the lower quartile: Q1.Step 3: Calculate IQR = Q3 - Q1.
To find the interquartile range (IQR) of a number set, first, arrange the data in ascending order. Next, identify the first quartile (Q1), which is the median of the lower half of the data, and the third quartile (Q3), the median of the upper half. Finally, subtract Q1 from Q3 (IQR = Q3 - Q1) to determine the range of the middle 50% of the data.
Interquartile deviation Qd=(q3-q1) / 2
procedure: step 1: arrange your raw data in increasing order. step 2: find the Q1 is the size of the (n+1)/4th value. step 3: find the Q3 is the size of the 3(n+1)/4th value. Quartile Deviation(QD)= (Q3-Q1)/2 for example: 87 ,64,74,13,19,27,60,51,53,29,47 is the given data step 1: 13,19,27,29,47,51,53,60,64,74,87 step 2: (n+1)/4=3 therefore Q1=27 step 3: 3(n+1)/4=9 therefore Q3=6 implies QD=18.5
The quartile deviation(QD) is half the difference between the highest and lower quartile in a distribution.
There is no agreed definition of outliers. However two common criteria to identify outliers are: Method I: If Q1 is the lower quartile and Q3 the upper quartile then any number smaller than Q1 - 1.5*(Q3 - Q1) or larger than Q3 + 1.5*(Q3 - Q1) is an outlier. By that criterion there is no outlier. Method II: Assume the numbers are normally distributed. then outliers are with absolute z-scores greater than 1.96. Again, there are no outliers.
first quartile (Q1) : Total number of term(N)/4 = Nth term third quartile (Q3): 3 x (N)/4th term