histogramKurtosis is a measure of the combined sizes of the two tails. It measures the amount of probability in the tails. The value is often compared to the kurtosis of the normal distribution, which is equal to 3. If the kurtosis is greater than 3, then the dataset has heavier tails than a normal distribution (more in the tails). If the kurtosis is less than 3, then the dataset has lighter tails than a normal distribution (less in the tails). Careful here. Kurtosis is sometimes reported as “excess kurtosis.” Excess kurtosis is determined by subtracting 3 form the kurtosis. This makes the normal distribution kurtosis equal 0. Kurtosis originally was thought to measure the peakedness of a distribution. Though you will still see this as part of the definition in many places, this is a misconception.
Kurtosis is a measure of the combined sizes of the two tails in a histogram. It calculates how much probability is in the tails. The value is frequently compared to the normal distribution's kurtosis, which is equal to 3. The dataset has larger tails than a normal distribution if the kurtosis is greater than 3. (more in the tails). The dataset exhibits lighter tails than a normal distribution if the kurtosis is less than 3. (less in the tails). Take care here. Kurtosis is frequently referred to as "extra kurtosis," which is calculated by subtracting three from the kurtosis. The kurtosis of the normal distribution is now 0. Kurtosis was originally supposed to be a metric for determining a distribution's peak.
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