The standard deviation alone does not measure relative variation. For example, a standard deviation of $1 would be considered large if it is describing the variability from store to store in the price of an ice cube tray. On the other hand, a standard deviation of $1 would be considered small if it is describing store-to-store variability in the price of a particular brand of freezer. A quantity designed to give a relative measure of variability is the coefficient of variation. Denoted by CV, the coefficient of variation expresses the standard deviation as a percentage of the mean. It is defined by the formula CV = 100(s/ x ). Consider two samples. Sample 1 gives the actual weight (in ounces) of the contents of cans of pet food labeled as having a net weight of 8 oz. Sample 2 gives the actual weight (in pounds) of the contents of bags of dry pet food labeled as having a net weight of 50 lb. There are weights for the two samples.
Sample 1 | 8.2 | 7.3 | 7.4 | 8.6 | 7.4 |
8.2 | 8.6 | 7.5 | 7.5 | 7.1 | |
Sample 2 | 51.8 | 51.2 | 51.9 | 51.6 | 52.7 |
47 | 50.4 | 50.3 | 48.7 | 48.2 |
(a) For each of the given samples, calculate the mean and the standard deviation. (Round all intermediate calculations and answers to five decimal places.)
For sample 1 | |
Mean | |
Standard deviation |
For sample 2 | |
Mean | |
Standard deviation |
(b) Compute the coefficient of variation for each sample. (Round
all answers to two decimal places.)
CV1 | |
CV2 |
a).NECESSARY CALCULATION FOR MEAN AND VARIANCE:-
table 1: calculation for mean:-
sample 1() | sample 2() |
8.2 | 51.8 |
7.3 | 51.2 |
7.4 | 51.9 |
8.6 | 51.6 |
7.4 | 52.7 |
8.2 | 47 |
8.6 | 50.4 |
7.5 | 50.3 |
7.5 | 48.7 |
7.1 | 48.2 |
sum=77.8 | sum=503.8 |
so, we have:-
table 2: calculation of sd:-
sample 1() | sample 2() | ||
8.2 | 51.8 | 0.1764 | 2.0164 |
7.3 | 51.2 | 0.2304 | 0.6724 |
7.4 | 51.9 | 0.1444 | 2.3104 |
8.6 | 51.6 | 0.6724 | 1.4884 |
7.4 | 52.7 | 0.1444 | 5.3824 |
8.2 | 47 | 0.1764 | 11.4244 |
8.6 | 50.4 | 0.6724 | 0.0004 |
7.5 | 50.3 | 0.0784 | 0.0064 |
7.5 | 48.7 | 0.0784 | 2.8224 |
7.1 | 48.2 | 0.4624 | 4.7524 |
sum=2.836 | sum=30.876 |
so, we have:-
THE MEAN AND STANDARD DEVIATION TABLE BE:-
sample 1 | sample 2 | |
mean | 7.78 | 50.38 |
standard deviation | 0.56135 | 1.85221 |
b). coefficient of variation be:-
calculation | answer | |
sample 1 |
% |
CV1 = 7.22 % |
sample 2 |
% |
CV2 = 3.68 % |
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