The coefficient of variation CV describes the standard deviation as a percent of the mean. Because it has no units, you can use the coefficient of variation to compare data with different units. Find the coefficient of variation for each sample data set. What can you conclude? CV = Standard deviation / Mean • 100% Heights Weights 65 198 65 210 66 220 67 226 80 168 74 184 74 179 71 221 69 181 65 187 76 230 72 168
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
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Heights
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Weights
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65
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198
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65
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210
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66
|
220
|
67
|
226
|
80
|
168
|
74
|
184
|
74
|
179
|
71
|
221
|
69
|
181
|
65
|
187
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76
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230
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72
|
168
|
Given Information:
The coefficient of variation CV describes the standard deviation as a percent of the mean.
It is given by the formula:
To find the coefficient of variation for each sample data set:
First compute the mean and standard deviation for each sample:
Heights:
Mean is the sum of observations divided by the total no. of observations. It is calculated as follows:
Standard deviation is calculated using the formula:
Substitute the values in the formula of Coefficient of variation:
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