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Skewness Percentage Formula:
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Skewness percentage is a statistical measure that quantifies the asymmetry of a probability distribution. It indicates whether data points are skewed to the left (negative skew) or right (positive skew) of the mean, expressed as a percentage for easier interpretation.
The calculator uses the skewness percentage formula:
Where:
Explanation: This formula compares the relationship between mean and median, normalized by the standard deviation to provide a standardized measure of distribution asymmetry.
Details: Understanding skewness helps identify distribution characteristics, detect outliers, and determine appropriate statistical methods. It's crucial in fields like finance, research, and quality control where normal distribution assumptions are important.
Tips: Enter the mean, median, and standard deviation values. All values must be numerical, and standard deviation must be greater than zero. The result shows skewness as a percentage, where positive values indicate right skew and negative values indicate left skew.
Q1: What does a skewness percentage of 0 mean?
A: A value of 0 indicates a perfectly symmetrical distribution where mean equals median.
Q2: How do I interpret positive vs. negative skewness?
A: Positive skewness indicates a right-skewed distribution (tail extends to right), while negative skewness indicates a left-skewed distribution (tail extends to left).
Q3: What is considered a significant skewness value?
A: Generally, values beyond ±10% may indicate notable skewness, but interpretation depends on the specific context and field of study.
Q4: How is this different from other skewness measures?
A: This percentage format provides an intuitive interpretation compared to dimensionless skewness coefficients, making it easier to communicate to non-technical audiences.
Q5: When should I be concerned about skewness?
A: Significant skewness may affect statistical analyses that assume normality, requiring data transformation or non-parametric methods.