Page 147 - DCOM203_DMGT204_QUANTITATIVE_TECHNIQUES_I

Quantitative Techniques – I

Notes Calculation of M.D.
Sum of observations which are greater than M
d
= 475 + 525 + 460 + 325 + 150 = 1,935
Sum of observations which are less than M
d
= 135 + 330 + 595 = 1060
No. of observations which are greater than M , i.e., k
d 2
= 10 +10 +8 +5 + 2 = 35
No. of observations which are less than M , i.e., k
d 1
= 6 +12 +17 = 35
.
1935 1060 8 75
M.D. = = 8.75 and the coefficient of M.D. = = 0.206
100 42 5
.
7.7.2 Merits and Demerits of Mean Deviation

Merits

1. It is easy to understand and easy to compute.
2. It is based on all the observations.

3. It is less affected by extreme observations vis-a-vis range or standard deviation (to be
discussed in the next section).
4. It is not much affected by fluctuations of sampling.

Demerits

1. It is not capable of further mathematical treatment. Since mean deviation is the arithmetic
mean of absolute values of deviations, it is not very convenient to be algebraically
manipulated.

2. This necessitates a search for a measure of dispersion which is capable of being subjected
to further mathematical treatment.
3. It is not well defined measure of dispersion since deviations can be taken from any measure
of central tendency.

Uses of M.D.

The mean deviation is a very useful measure of dispersion when sample size is small and no
elaborate analysis of data is needed. Since standard deviation gives more importance to extreme
observations the use of mean deviation is preferred in statistical analysis of certain economic,
business and social phenomena.

Task Calculate the Mean Deviation from mean as well as from median of first ten prime
numbers.

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