The KURT function in Excel returns the kurtosis of a data set, which measures the peakedness of the data values relative to a normal distribution. Kurtosis can be used to detect outliers in a data set.
Kurt Function MS Excel is a statistical tool used to measure a data set’s tail weight. The tail weight of a data set describes the degree to which its distribution is more or less peaked than a normal distribution. The function can be used to analyze the distribution of data in a range of cells and to determine if the data is skewed or has outliers.
The KURT formula takes four arguments: the range of cells containing the data, the number of observations, the number of variables, and the mean of the data set. The function will then return a value between -3 and +3, which indicates the degree to which the data distribution is more or less peaked than a normal distribution.
A value closer to -3 indicates that the data is more platykurtic or less peaked and indicates a distribution with more extreme values.
A value closer to +3 indicates that the data is more leptokurtic, or more peaked, and is indicative of a data set with fewer extreme values.
Kurt function can help you identify outliers and skewness. It can be used to gain insight into the underlying structure of a data set and compare data sets to each other. Function can identify the most important variables in a data set and identify relationships between variables.
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KURT(number1, [number2], …)
number1: A numeric value or range of values.
[number2], …: Optional additional numeric values or ranges of values.
Excel can report kurtosis, but not excess kurtosis.
Kurtosis is a measure of the “peakedness” of a distribution. It is a measure of the concentration of values at the center of the distribution. Higher kurtosis indicates higher concentration of values at the center with fewer values at the tails, thus creating a more peaked distribution. Low kurtosis indicates fewer values at the center and more at the tails, creating a flatter distribution.
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