kurtosis statistics

1. Presented By: Rishi Ram Khanal
BIM (TU)
Presentation on Kurtosis
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2. contents
 Definition of Kurtosis
 Types of Kurtosis
Mesokurtic
distribution
Leptokurtic
distribution
Platykurtic distribution
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3. kurtosis
 Kurtosis is a statistical measures, used to
describe the distribution, or skewness.
 It observed data around the mean, sometimes
referred to as the volatility of volatility.
 Kurtosis is used generally in the statistical field to
describes trends in charts.
 Kurtosis can be present in a chart with fat tails
and a low, even distribution, as well as be present
in a chart with skinny tails and a distribution
concentrated toward the mean.
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5. Mesokurtic distribution
 The first category of kurtosis is
a mesokurtic distribution.
 This type of kurtosis is the most similar to a
standard normal distribution in that it also
resembles a bell curve.
 However, a graph that is mesokurtic has fatter
tails than a standard normal distribution and has
a slightly lower peak.
 This type of kurtosis is considered normally
distributed but is not a standard normal
distribution.
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6. Leptokurtic distribution
 The second category is a leptokurtic distribution.
 Any distribution that is leptokurtic displays
greater kurtosis than a mesokurtic distribution.
 Characteristics of this type of distribution is one
with extremely thick tails and a very thin and tall
peak.
 The prefix of "lepto-" means "skinny," making the
shape of a leptokurtic distribution easier to
remember.
 T-distributions are leptokurtic.
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7. Platykurtic distribution
 The final type of distribution is a platykurtic
distribution.
 These type of distributions have slender tails and
a peak that's smaller than a mesokurtic
distribution.
 The prefix of "platy-" means "broad," and it is
meant to describe a short and broad-looking
peak.
 Uniform distributions are platykurtic.
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