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Consider the following sets of sample data: A: 431, 447, 306, 413, 315, 432, 312, 387, 295, 327, 323, 296, 441, 312 B: $1.35, $1.82, $1.82, $2.72, $1.07, $1.86, $2.71, $2.61, $1.13, $1.20, $1.41 Step 1 of 2 : For each of the above sets of sample data, calculate the coefficient of variation, CV. Round to one decimal place.

User Fiacobelli
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Answer:

Dataset A

We have the following results:


\bar X_A = 359.786


s_A= 60.904


CV_A = (60.904)/(359.786)= 0.169 \approx 0.2

Dataset B

We have the following results:


\bar X_B = 1.791


s_B= 0.635


CV_B = (0.635)/(1.791)= 0.355 \approx 0.4

Explanation:

For this case we have the following info given:

A: 431, 447, 306, 413, 315, 432, 312, 387, 295, 327, 323, 296, 441, 312

B: $1.35, $1.82, $1.82, $2.72, $1.07, $1.86, $2.71, $2.61, $1.13, $1.20, $1.41

We need to remember that the coeffcient of variation is given by this formula:


CV= (s)/(\bar X)

Where the sample mean is given by:


\bar X= (\sum_(i=1)^n X_i)/(n)

And the sample deviation given by:


s=\sqrt{(\sum_(i=1)^n (X_i -\bar X)^2)/(n-1)}

Dataset A

We have the following results:


\bar X_A = 359.786


s_A= 60.904


CV_A = (60.904)/(359.786)= 0.169 \approx 0.2

Dataset B

We have the following results:


\bar X_B = 1.791


s_B= 0.635


CV_B = (0.635)/(1.791)= 0.355 \approx 0.4

User Gary Kerr
by
8.0k points
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