Skewness and Kurtosis in R
A distribution's symmetry is measured by its skewness. If there is a greater concentration of data on one side of the mean than the other, this is indicated. For a symmetric distribution, the mode, median, and mean are all equal, and the skewness value is 0. Data is skewed towards higher values when there is positive skewness (greater than zero), which is indicative of a longer tail on the right side of the distribution. When there is less than zero negative skewness, the data is skewed towards lower values because the distribution's tail is longer on the left.
Kurtosis quantifies how flat or peaky the distribution is. It shows the degree to which the data is significantly peaked around the mean. A normal distribution is shown by a zero kurtosis value. Leptokurtosis, another name for positive kurtosis (more than zero), denotes a distribution with fatter tails and a higher peak than a normal distribution. When a distribution exhibits platykurtosis, or negative kurtosis (less than zero), it means that, in comparison to a normal distribution, it has thinner tails and a lower peak.