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Part 3 of 5 Calculate the Pearson's index of skewness. (Round the mean, median and standard deviation to one decimal place and Pearson's index to two decimal places.) It can be concluded that the distribution is not significantly \( \boldsymbol{\nabla} \) skewed.

Ask by Morrison Frank. in the United States
Mar 10,2025

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The Pearson's index of skewness is 0, indicating that the distribution is not significantly skewed.

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To calculate the Pearson's index of skewness, we need to follow these steps: 1. Calculate the mean of the data. 2. Calculate the median of the data. 3. Calculate the standard deviation of the data. 4. Calculate the Pearson's index of skewness using the formula: \[ \text{Pearson's Index of Skewness} = \frac{\text{Mean} - \text{Median}}{\text{Standard Deviation}} \] Let's assume we have the following data: 2, 4, 6, 8, 10. 1. Calculate the mean of the data: \[ \text{Mean} = \frac{2 + 4 + 6 + 8 + 10}{5} = \frac{30}{5} = 6 \] 2. Calculate the median of the data: Since the data is already sorted, the median is the middle value, which is 6. 3. Calculate the standard deviation of the data: \[ \text{Standard Deviation} = \sqrt{\frac{\sum_{i=1}^{n} (x_i - \text{Mean})^2}{n}} \] \[ \text{Standard Deviation} = \sqrt{\frac{(2-6)^2 + (4-6)^2 + (6-6)^2 + (8-6)^2 + (10-6)^2}{5}} \] \[ \text{Standard Deviation} = \sqrt{\frac{16 + 4 + 0 + 4 + 16}{5}} \] \[ \text{Standard Deviation} = \sqrt{\frac{40}{5}} \] \[ \text{Standard Deviation} = \sqrt{8} \] \[ \text{Standard Deviation} = 2.828 \] 4. Calculate the Pearson's index of skewness: \[ \text{Pearson's Index of Skewness} = \frac{6 - 6}{2.828} = 0 \] Therefore, the Pearson's index of skewness is 0, indicating that the distribution is not significantly skewed.

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To calculate Pearson's index of skewness, you can use the formula: \[ Sk = \frac{3(\text{Mean} - \text{Median})}{\text{Standard Deviation}} \] The value of the skewness will indicate the asymmetry of the distribution. If the skewness is close to 0, this suggests a symmetrical distribution. A positive skew indicates a right tail, while a negative skew indicates a left tail. Keep in mind that the closer the skewness is to zero, the more normally distributed your data is likely to be. If you find yourself confounded by calculations, remember to double-check your figures! Common pitfalls include mixing up the mean, median, and standard deviation values or miscalculating their values due to rounding errors. Make sure each is rounded to one decimal place first before using them in the skewness formula!

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