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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 \begin{tabular}{l} (Choose one) \\ significantly \\ not significantly \\ \hline\end{tabular}

Ask by Ayala Todd. in the United States
Mar 08,2025

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

Solution

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 the data is: 1, 2, 3, 4, 5 1. Calculate the mean: \[ \text{Mean} = \frac{1 + 2 + 3 + 4 + 5}{5} = \frac{15}{5} = 3 \] 2. Calculate the median: Since the data is already sorted, the median is the middle value, which is 3. 3. Calculate the standard deviation: \[ \text{Standard Deviation} = \sqrt{\frac{\sum_{i=1}^{n} (x_i - \text{Mean})^2}{n}} \] \[ \text{Standard Deviation} = \sqrt{\frac{(1-3)^2 + (2-3)^2 + (3-3)^2 + (4-3)^2 + (5-3)^2}{5}} \] \[ \text{Standard Deviation} = \sqrt{\frac{4 + 1 + 0 + 1 + 4}{5}} \] \[ \text{Standard Deviation} = \sqrt{\frac{10}{5}} \] \[ \text{Standard Deviation} = \sqrt{2} \] 4. Calculate the Pearson's index of skewness: \[ \text{Pearson's Index of Skewness} = \frac{3 - 3}{\sqrt{2}} = 0 \] Since the Pearson's index of skewness is 0, it indicates that the distribution is not significantly skewed. Therefore, the distribution is not significantly skewed.

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To calculate Pearson's index of skewness, you first need the mean, median, and standard deviation of your data set. The formula for Pearson's index of skewness (often denoted as SK) is: \[ SK = 3 \times \frac{(\text{Mean} - \text{Median})}{\text{Standard Deviation}} \] Once you've calculated this, you can interpret the skewness. If the index is greater than 0, the distribution is positively skewed (the tail on the right side is longer or fatter). If it’s less than 0, it’s negatively skewed (the tail on the left side is longer or fatter). If it’s close to 0, the distribution is approximately symmetric. A skewness index of |SK| > 1 indicates significant skewness, while |SK| between 0.5 and 1 denotes moderate skewness, and |SK| < 0.5 suggests a distribution that is fairly symmetrical. Get out those calculators and have fun exploring the data!

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