Description: The SKEW function calculates the skewness of a distribution, providing a measure that indicates whether the data is symmetrically distributed or if it has biases towards one side. In statistical terms, skewness refers to the lack of symmetry in the distribution of a dataset. A symmetric distribution has a skewness of zero, meaning that values are evenly distributed around the mean. However, if the skewness is positive, it indicates that there is a longer tail on the right side of the distribution, suggesting that there are more extreme high values. Conversely, negative skewness indicates that the tail is longer on the left side, suggesting the presence of extreme low values. Skewness is an important characteristic in data analysis, as it can influence the interpretation of the mean and median, as well as the choice of appropriate statistical methods for analysis. Understanding the skewness of a distribution allows analysts and statisticians to make informed decisions about the nature of the data and the inferences that can be drawn from it.
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