š Kurtosis Calculator
Evaluate tail behaviour and peakedness by calculating excess kurtosis (Fisher gā). Paste numeric data to obtain kurtosis, variance, and practical interpretation of leptokurtic vs. platykurtic tendencies.
Dataset Input
Invalid tokens are ignored. Paste from spreadsheets or CSV files.
Excess Kurtosis (gā)
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Classical Kurtosis (Ī²ā)
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Sample Std. Dev.
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Count
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Fourth Central Moment
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Second Central Moment
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Interpretation
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Insights
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How to Use
- Paste or type your dataset into the values field.
- Click Calculate Kurtosis to obtain excess kurtosis, classical kurtosis, standard deviation, and central moments.
- Review the interpretation to determine if the distribution is leptokurtic (heavy-tailed) or platykurtic (light-tailed).
- Use insights to identify whether the dataset is near-normal (excess ā 0) or exhibits significant tail behaviour.
- Clean or reset data when analysing new samples.
Formula Reference
Sample excess kurtosis (Fisher): \( g_2 = \frac{n(n+1)}{(n-1)(n-2)(n-3)} \sum \left( \frac{x_i - \bar{x}}{s} \right)^4 - \frac{3(n-1)^2}{(n-2)(n-3)} \). Reference: Joanes & Gill (1998), "Comparing Measures of Sample Skewness and Kurtosis".