Part: \( 2 / 5 \) 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 Skip Part skewed. Recheck
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Bonus Knowledge
To calculate Pearson's index of skewness, you will need the mean, median, and standard deviation of your dataset. The formula for Pearson’s index of skewness (commonly referred to as "Pearson's First Coefficient of Skewness") is: \[ Skewness = \frac{3(\text{Mean} - \text{Median})}{\text{Standard Deviation}} \] Once you have obtained the mean, median, and standard deviation (all rounded to one decimal place), plug those values into the formula. If your calculated skewness value is close to 0, it indicates that the distribution is not significantly skewed. A skewness value greater than 1 or less than -1 typically suggests a significant skew in the distribution. Now that you understand the calculation, make sure to double-check your calculations and rounding to ensure accurate results—rounding can sometimes lead to unexpected interpretations!
