Statistics – Co-efficient of Variation

Coefficient of Variation

Standard variation is an absolute measure of dispersion. When comparison has to be made between two series then the relative measure of dispersion, known as coeff.of variation is used.

Coefficient of Variation, CV is defined and given by the following function:

Formula

CV=σX×100CV=σX×100

Where −

·        CVCV = Coefficient of Variation.

·        σσ = standard deviation.

·        XX = mean.

Example

Problem Statement:

From the following data. Identify the risky project, is more risky:

Year12345
Project X (Cash profit in Rs. lakh)1015253055
Project Y (Cash profit in Rs. lakh)520404030

Solution:

In order to identify the risky project, we have to identify which of these projects is less consistent in yielding profits. Hence we work out the coefficient of variation.

Project XProject y
XXXi−X¯Xi−X¯ 
xx
x2x2YYYi−Y¯Yi−Y¯ 
yy
y2y2
10-172895-22484
15-1214420-749
25-244013169
30394013169
55287843039
∑X=135∑X=135 ∑x2=1230∑x2=1230∑Y=135∑Y=135 ∑y2=880∑y2=880

Project X

Here X¯=∑XN=∑1355=27and σx=∑X2N−−−−√⇒σx=12305−−−−√=246−−−√=15.68⇒CVx=σxX×100=15.6827×100=58.07Here X¯=∑XN=∑1355=27and σx=∑X2N⇒σx=12305=246=15.68⇒CVx=σxX×100=15.6827×100=58.07

Project Y

Here Y¯=∑YN=∑1355=27and σy=∑Y2N−−−−√⇒σy=8805−−−√=176−−−√=13.26⇒CVy=σyY×100=13.2527×100=49.11Here Y¯=∑YN=∑1355=27and σy=∑Y2N⇒σy=8805=176=13.26⇒CVy=σyY×100=13.2527×100=49.11

Since coeff.of variation is higher for project X than for project Y, hence despite the average profits being same, project X is more risky.

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