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? Standard deviation CV= • 100% Mean Click the icon to view the data sets. Data table (Round to the nearest tenth as needed.) CV heights Heights Weights 80 219 76 210 77 179 70 225 80 176 67 168 78 203 65 222 65 228 69 178 72 180 66 176

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
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Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 15PPS
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What is the CVweights
### Understanding Coefficient of Variation (CV)

The coefficient of variation (CV) describes the standard deviation as a percent of the mean. Since it has no units, you can use the coefficient of variation to compare data with different units. Below is the formula to calculate the coefficient of variation:

\[ \text{CV} = \left( \frac{\text{Standard deviation}}{\text{Mean}} \right) \times 100\% \]

### Data Table
Below is a data table that consists of heights and weights of individuals:

| Heights (inches) | Weights (pounds) |
|:----------------:|:----------------:|
| 80               | 219              |
| 76               | 210              |
| 77               | 179              |
| 70               | 225              |
| 80               | 176              |
| 67               | 168              |
| 78               | 203              |
| 65               | 222              |
| 65               | 228              |
| 69               | 178              |
| 72               | 180              |
| 66               | 176              |

### Instruction
- **To calculate the CV:** 
  1. Compute the standard deviation and the mean for the desired dataset (Heights or Weights).
  2. Use the formula provided to find the coefficient of variation.
  3. Round the CV value to the nearest tenth as needed.

This allows for a comparison of the variability of different datasets even if their units differ. 

### Graph/Diagram Explanation
There is no specific graph or diagram shown in the image, but the data table provides the necessary figures to calculate the coefficient of variation for both heights and weights. 

- **Standard deviation**: Measure of the amount of variation or dispersion in a set of values.
- **Mean**: Average value of a set of numbers.

By calculating the CV for the given datasets, you can determine which dataset has more relative variability, aiding in more insightful statistical analysis.
Transcribed Image Text:### Understanding Coefficient of Variation (CV) The coefficient of variation (CV) describes the standard deviation as a percent of the mean. Since it has no units, you can use the coefficient of variation to compare data with different units. Below is the formula to calculate the coefficient of variation: \[ \text{CV} = \left( \frac{\text{Standard deviation}}{\text{Mean}} \right) \times 100\% \] ### Data Table Below is a data table that consists of heights and weights of individuals: | Heights (inches) | Weights (pounds) | |:----------------:|:----------------:| | 80 | 219 | | 76 | 210 | | 77 | 179 | | 70 | 225 | | 80 | 176 | | 67 | 168 | | 78 | 203 | | 65 | 222 | | 65 | 228 | | 69 | 178 | | 72 | 180 | | 66 | 176 | ### Instruction - **To calculate the CV:** 1. Compute the standard deviation and the mean for the desired dataset (Heights or Weights). 2. Use the formula provided to find the coefficient of variation. 3. Round the CV value to the nearest tenth as needed. This allows for a comparison of the variability of different datasets even if their units differ. ### Graph/Diagram Explanation There is no specific graph or diagram shown in the image, but the data table provides the necessary figures to calculate the coefficient of variation for both heights and weights. - **Standard deviation**: Measure of the amount of variation or dispersion in a set of values. - **Mean**: Average value of a set of numbers. By calculating the CV for the given datasets, you can determine which dataset has more relative variability, aiding in more insightful statistical analysis.
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