Kurtosis Calculator
Analyze the tailedness of your data distribution. Enter values and probabilities to calculate kurtosis.
Kurtosis Result:
Kurtosis measures the "tailedness" of the probability distribution.
- Kurtosis ≈ 3 (Excess Kurtosis ≈ 0): Mesokurtic (similar to normal distribution).
- Kurtosis < 3 (Excess Kurtosis < 0): Platykurtic (flatter distribution with thinner tails).
- Kurtosis > 3 (Excess Kurtosis > 0): Leptokurtic (peaked distribution with fatter tails).
Probability Density Function Visualization
Visualization of the Probability Density Function (PDF) based on provided values and probabilities. The shape illustrates the distribution's kurtosis.
About Kurtosis
Kurtosis is a statistical measure that describes the shape of a probability distribution by quantifying its tailedness. In simpler terms, it indicates how often extreme values occur in a distribution. There are three types of kurtosis:
- Mesokurtic: Kurtosis is around 3 (excess kurtosis around 0). This is typical of a normal distribution.
- Platykurtic: Kurtosis is less than 3 (excess kurtosis is negative). Distributions are flatter with thinner tails than a normal distribution.
- Leptokurtic: Kurtosis is greater than 3 (excess kurtosis is positive). Distributions are more peaked with fatter tails than a normal distribution, indicating more outliers.
- \( X \) is the random variable.
- \( \mu \) is the mean of the distribution.
- \( \sigma \) is the standard deviation of the distribution.
- \( E[\cdot] \) is the expectation operator.