Contents
Why normal distribution kurtosis is 3?
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).
What is the kurtosis of standard normal distribution?
2.3. A standard normal distribution has kurtosis of 3 and is recognized as mesokurtic. An increased kurtosis (>3) can be visualized as a thin “bell” with a high peak whereas a decreased kurtosis corresponds to a broadening of the peak and “thickening” of the tails. Kurtosis >3 is recognized as leptokurtic and <3.
What happens when kurtosis is zero?
When kurtosis is equal to 0, the distribution is mesokurtic. This means the kurtosis is the same as the normal distribution, it is mesokurtic (medium peak). The kurtosis of a mesokurtic distribution is neither high nor low, rather it is considered to be a baseline for the two other classifications.
How do you calculate kurtosis?
Click on Analyze -> Descriptive Statistics -> Descriptives
What does the kurtosis tell us?
Kurtosis tell us about the peakdness or flaterness of the distribution. Kurtosis is basically statistical measure that helps to identify the data around the mean.
What does negative value of kurtosis mean?
Negative values of kurtosis indicate that a distribution is flat and has thin tails. Platykurtic distributions have negative kurtosis values. A platykurtic distribution is flatter (less peaked) when compared with the normal distribution, with fewer values in its shorter (i.e. lighter and thinner) tails.
What does a negative kurtosis indicate?
A distribution with a negative kurtosis value indicates that the distribution has lighter tails and a flatter peak than the normal distribution. For example, data that follow a beta distribution with first and second shape parameters equal to 2 have a negative kurtosis value.