Contents
What is a kurtosis tail?
Kurtosis is a measure of the combined weight of a distribution’s tails relative to the center of the distribution. When a set of approximately normal data is graphed via a histogram, it shows a bell peak and most data within three standard deviations (plus or minus) of the mean.
What does it mean if kurtosis is above 3?
Kurtosis is a measure of the combined sizes of the two tails. If the kurtosis is greater than 3, then the dataset has heavier tails than a normal distribution (more in the tails). If the kurtosis is less than 3, then the dataset has lighter tails than a normal distribution (less in the tails).
Is positive kurtosis good?
When excess kurtosis is positive, it has a leptokurtic distribution. The tails on this distribution is heavier than that of a normal distribution, indicating a heavy degree of risk. The returns on an investment with a leptokurtic distribution or positive excess kurtosis will likely have extreme values.
What are the tails of a low kurtosis distribution?
Distributions with low kurtosis exhibit tail data that are generally less extreme than the tails of the normal distribution.
What are the different types of kurtosis in psychology?
Kurtosis is a statistical measure used to describe the degree to which scores cluster in the tails or the peak of a frequency distribution. The peak is the tallest part of the distribution, and the tails are the ends of the distribution. There are three types of kurtosis: mesokurtic, leptokurtic, and platykurtic.
Which is the tallest part of the kurtosis?
The peak is the tallest part of the distribution, and the tails are the ends of the distribution. There are three types of kurtosis: mesokurtic, leptokurtic, and platykurtic.
What does it mean when kurtosis is positive?
What does it mean when kurtosis is positive? Positive values of kurtosis indicate that a distribution is peaked and possess thick tails. Leptokurtic distributions have positive kurtosis values. A leptokurtic distribution has a higher peak and taller (i.e. fatter and heavy) tails than a normal distribution.