1. What Is The Skewness Index?

The skewness index is a measure of the asymmetry of a probability distribution. A positive skewness indicates a distribution with an asymmetric tail extending toward more positive values, while a negative skewness indicates a distribution that extends toward more negative values.

2. How Does The Calculator Work?

The calculator uses the skewness formula:

Where:

• \( Mean \) — Arithmetic mean of the dataset
• \( Median \) — Middle value of the dataset
• \( SD \) — Standard deviation of the dataset

Explanation: This formula provides a simple measure of distribution asymmetry based on the relationship between mean, median and standard deviation.

3. Importance Of Skewness Calculation

Details: Skewness is important in statistics to understand the shape of data distribution, identify outliers, and determine appropriate statistical methods for analysis.

4. Using The Calculator

Tips: Enter the mean, median, and standard deviation values. All values must be valid (SD > 0). The result is unitless and indicates the direction and degree of skewness.

5. Frequently Asked Questions (FAQ)

Q1: What does a skewness value of 0 mean?
A: A skewness value of 0 indicates a perfectly symmetrical distribution where the mean equals the median.

Q2: What is considered a significant skewness value?
A: Generally, a skewness value greater than +1 or less than -1 indicates a substantially skewed distribution.

Q3: How does skewness affect data analysis?
A: Highly skewed data may require transformation or non-parametric statistical tests for accurate analysis.

Q4: Are there other methods to calculate skewness?
A: Yes, other formulas include Pearson's first coefficient and the Fisher-Pearson standardized moment coefficient.

Q5: When should I be concerned about skewness?
A: Skewness becomes important when it affects the validity of statistical assumptions, particularly in parametric tests that assume normality.