Understanding Skewness in Probability Distributions | When the Coefficient of Skewness is Zero

If the coefficient of skewness is equal to zero, the shape of the distribution is ___A) Negatively skewedB) Symmetric C) Positively skewedD) Unknown

If the coefficient of skewness is equal to zero, the shape of the distribution is B) Symmetric

If the coefficient of skewness is equal to zero, the shape of the distribution is B) Symmetric.

Skewness is a statistical measure that indicates the asymmetry of a probability distribution. It tells us whether the probability distribution is leaning towards one direction (positively skewed), the other direction (negatively skewed), or if it is symmetric.

The coefficient of skewness can take on different values: positive, negative, or zero.

– If the coefficient of skewness is positive, it indicates that the distribution has a long tail on the right side, and therefore it is positively skewed.

– If the coefficient of skewness is negative, it indicates that the distribution has a long tail on the left side, and therefore it is negatively skewed.

– If the coefficient of skewness is equal to zero, it means that the distribution has equal amounts of data on both sides of the center, and thus it is symmetric.

Therefore, when the coefficient of skewness is equal to zero, the shape of the distribution is symmetric.

More Answers:
Exploring the Basics | An Introduction to Descriptive Statistics for Data Analysis
Inferential Statistics | Making Predictions and Drawing Conclusions through Sample Analysis
Understanding Measures of Dispersion | Range, Standard Deviation, and Interquartile Range

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