What does the kurtosis value mean?
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What does the kurtosis value mean?
Kurtosis is all about the tails of the distribution — not the peakedness or flatness. It is used to describe the extreme values in one versus the other tail. It is actually the measure of outliers present in the distribution . High kurtosis in a data set is an indicator that data has heavy tails or outliers.
What is kurtosis in simple words?
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.
How does kurtosis affect mean?
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).
How kurtosis is measured?
In statistics, a measure of kurtosis is a measure of the “tailedness” of the probability distribution of a real-valued random variable. The standard measure of kurtosis is based on a scaled version of the fourth moment of the data or population. A distribution having a relatively high peak is called leptokurtic.
What is the kurtosis of a normal distribution?
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.
How do you get kurtosis?
Kurtosis = Fourth Moment / Second Moment2
- Kurtosis = 313209 / (365)2
- Kurtosis = 2.35.
What is a good kurtosis value?
The values for asymmetry and kurtosis between -2 and +2 are considered acceptable in order to prove normal univariate distribution (George & Mallery, 2010).
What causes kurtosis?
A high kurtosis is more often caused by processes that directly contribute to a high peak, than by processes that directly contribute to fat tails. In fact, a high kurtosis is more often caused by processes that directly contribute to a high peak, than by processes that directly contribute to fat tails.
How does kurtosis affect data?
A distribution with a positive kurtosis value indicates that the distribution has heavier tails and a sharper peak than the normal distribution. For example, data that follow a t distribution have a positive kurtosis value.
What is a good kurtosis?
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.
How is kurtosis measured?
What is a kurtosis in statistics?
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.
How does kurtosis affect the risk of an investment?
A large kurtosis is associated with a high risk for an investment because it indicates high probabilities of extremely large and extremely small returns. On the other hand, a small kurtosis signals a moderate level of risk because the probabilities of extreme returns are relatively low.
How does kurtosis affect tail data?
Distributions with large kurtosis exhibit tail data exceeding the tails of the normal distribution (e.g., five or more standard deviations from the mean). Distributions with low kurtosis exhibit tail data that are generally less extreme than the tails of the normal distribution.
What is platykurtic kurtosis?
Whenever the kurtosis is less than zero or negative, it refers to Platykurtic. The distribution set follows the subtle or pale curve, and that curve indicates the small number of outliers in a distribution. An investment falling under platykurtic is usually demanded by investors because of a small probability of generating an extreme return.
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