Merits
· It can be easily calculated and simply understood.
· It does not involve much mathematical difficulties.
· As it takes middle 50% terms hence it is a measure better than Range and percentile Range.
· It is not affected by extreme terms as 25% of upper and 25% of lower terms are left out.
· Quartile Deviation also provides a short cut method to calculate Standard Deviation using the formula 6 Q.D. = 5 M.D. = 4 S.D.
· In case we are to deal with the centre half of a series this is the best measure to use.
Demerits or Limitations
· As Q1 and Q3 are both positional measures hence are not capable of further algebraic treatment.
· Calculation are much more, but the result obtained is not of much importance.
· It is too much affected by fluctuations of samples.
· 50% terms play no role; first and last 25% items ignored may not give reliable result.
· If the values are irregular, then result is affected badly.
· We can't call it a measure of dispersion as it does not show the scatter-ness around any average.
· The value of quartile may be same for two or more series or Q.D. is not affected by the distribution of terms between Q1 and Q3 or outside these positions.
So going through the merits and demerits, we conclude that Quartile Deviation cannot be relied on blindly. In the case of distributions with high degree of variation, quartile deviation has less reliability.
What is coefficient of quartile deviation?
mean deviation =(4/5)quartile deviation
In a data sample, the purpose of quartile deviation is a way to measure data dispersion instead of using the range. The quartile deviation is found by subtracting the lower quartile from the upper quartile, and dividing this result by two.
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coefficient of quartile deviation: (Q3-Q1)/(Q3+Q1)
What is coefficient of quartile deviation?
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