02
Nov
Define Kurtosis In Statistics. That is data sets with high kurtosis tend to have heavy tails or outliers. 95 percent of these kurtosis values fell between 244 and 377. Kurtosis_in_Statistics Statistics Shakehand_with_LifeKurtosis in statistics is the measure of the degree of peakedness of the frequency distribution curve. The peak is the tallest part of the distribution and the tails are the ends of the distribution.
Many books say that these two statistics give you insights into the shape of the distribution. Kurtosis is a statistical measure used to describe the degree to which scores cluster in the tails or the peak of a frequency distribution. In other words kurtosis identifies whether the tails of a given distribution contain extreme values. Data sets with low kurtosis tend to have light tails or lack of outliers. The peak is the tallest part of the distribution and the tails are the ends of the distribution. It tells us the extent to which the distribution is more or less outlier-prone heavier or l.
Therefore the measure of kurtosis is related to the tails of the distribution not its peak.
In statistics a measure of kurtosis is a measure of the tailedness of the probability distribution of a real-valued random variable. Data sets with low kurtosis tend to have light tails or lack of outliers. Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution. Definition of Kurtosis In statistics kurtosis is defined as the parameter of relative sharpness of the peak of the probability distribution curve. Kurtosis_in_Statistics Statistics Shakehand_with_LifeKurtosis in statistics is the measure of the degree of peakedness of the frequency distribution curve. 95 percent of these kurtosis values fell between 244 and 377.