Geostatistics: Coefficient of Variation and Kurtosis

Measures of Dispersion and Distribution Shape

• The coefficient of variation (CV) is a statistical measure used to assess the relative variability of a dataset in relation to its mean value.
• CV is useful for comparing the variability of different datasets with different units or scales.

Kurtosis

• Kurtosis measures the tailedness or peakedness of a distribution, with high kurtosis indicating a more peaked distribution and low kurtosis indicating a flatter distribution.

Coefficient of Variation (CV)

• A CV greater than 1 indicates that the standard deviation is greater than the mean, which can occur in cases where the data contains extreme outliers or a skewed distribution.

Distribution Shapes

• A meso-kurtic distribution represents a normal or bell-shaped curve, which is neither too peaked nor too flat.

Skewness

• Skewness values can be interpreted as follows:
  • Positive skewness indicates a distribution with a long tail to the right.
  • Negative skewness indicates a distribution with a long tail to the left.
  • A skewness value close to zero indicates a relatively symmetrical distribution.

Test your knowledge of coefficient of variation, kurtosis, meso-kurtic, platy-kurtic, and lepto-kurtic distributions, and how to interpret kurtosis values. This quiz covers numerical measures of curve shape and skewness in the context of applied geophysics and geology.