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Skewness and kurtosis are important statistical measures used to understand the shape and characteristics of a probability distribution. While mean and variance describe the central location and spread of data, skewness and kurtosis provide additional information about the symmetry and tail behaviour of a distribution. Therefore, two datasets can have the same mean and variance but still have substantially different distributional patterns. Skewness measures the degree and direction of asymmetry in a distribution around its mean. A perfectly symmetric distribution has zero skewness. Positive skewness indicates that the distribution has a longer or _____ ________ ____ _________ __________ __________ _________ _________.
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