Difference between revisions of "Manuals/calci/KURT"
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− | <div style="font-size:30px">'''KURT( | + | <div style="font-size:30px">'''KURT()'''</div><br/> |
− | * | + | *Parameters are any values to calculate kurtosis. |
+ | **KURT(), returns the kurtosis of a data set. | ||
==Description== | ==Description== | ||
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==ZOS== | ==ZOS== | ||
− | *The syntax is to calculate KURTOSIS in ZOS is <math>KURT( | + | *The syntax is to calculate KURTOSIS in ZOS is <math>KURT()</math> |
− | ** | + | **Parameters are any values to calculate kurtosis. |
− | *For e.g., | + | *For e.g., KURT([-1..-10,20..25..0.5]) |
{{#ev:youtube|YqusfrKpWEA|280|center|KURTOSIS}} | {{#ev:youtube|YqusfrKpWEA|280|center|KURTOSIS}} | ||
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! 4 | ! 4 | ||
| 26 ||16 || 12 || || | | 26 ||16 || 12 || || | ||
− | |||
− | |||
− | |||
|} | |} | ||
# =KURT(A1:E1) = -0.8704870491886512 | # =KURT(A1:E1) = -0.8704870491886512 | ||
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# =KURT(A3:D3) = 0.8709011137293157 | # =KURT(A3:D3) = 0.8709011137293157 | ||
# =KURT(A4:C4) = NAN | # =KURT(A4:C4) = NAN | ||
+ | |||
+ | ==Related Videos== | ||
+ | |||
+ | {{#ev:youtube|HnMGKsupF8Q|280|center|Kurtosis}} | ||
==See Also== | ==See Also== | ||
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==References== | ==References== | ||
[http://en.wikipedia.org/wiki/Kurtosis Kurtosis] | [http://en.wikipedia.org/wiki/Kurtosis Kurtosis] | ||
+ | |||
+ | |||
+ | *[[Z_API_Functions | List of Main Z Functions]] | ||
+ | |||
+ | *[[ Z3 | Z3 home ]] |
Latest revision as of 16:22, 7 August 2018
KURT()
- Parameters are any values to calculate kurtosis.
- KURT(), returns the kurtosis of a data set.
Description
- This function gives the value of Kurtosis of a given set.
- Kurtosis is the peak or flatness of a frequency distribution graph especially with respect to the concentration of values near the Mean as compared with the Normal Distribution.
- A normal distribution has a Kurtosis of 3.
- Distributions having higher Kurtosis have flatter tails or more extreme values that phenomenon called 'leptokurtosis' also it is the positive excess Kurtosis , and those with lower Kurtosis have fatter middles or fewer extreme value that phenomenon called 'Platykurtosis' also it is the negative excess Kurtosis.
- Example for positive Kurtosis(leptokurtosis) is Exponential distribution, Poisson distribution, Laplace Distribution.
- Example for Negative Kurtosis(platykurtosis) is Bernoulli distribution, Uniform distribution.
- Kurtosis has no units.
- Kurtosis is defined by:
- Kurtosis=:
, where is the Sample Standard Deviation. is the Arithmetic Mean.
- In this function arguments may be any type like numbers,names,arrays or references that contain numbers.
- We can give logical values and text references also directly.
- Suppose the referred argument contains any null cells, logical values like that values are not considered.
- This function will return the result as error when
1.Any one of the argument is non-numeric. 2.Suppose the number of data points are less than four or the standard deviation of the sample is zero 3.The referred arguments could not convert in to numbers.
- When calculating kurtosis, a result of +3.00 indicates the absence of kurtosis (distribution is mesokurtic).
- For simplicity in its interpretation, some statisticians adjust this result to zero (i.e. kurtosis minus 3 equals zero), and then any reading other than zero is referred to as excess kurtosis.
- Negative numbers indicate a platykurtic distribution and positive numbers indicate a leptokurtic distribution.
- The below table is listing the Kurtosis excess for the number of common distributions:
Distribution | Kurtosis excess |
---|---|
Bernoulli distribution | |
Beta distribution | |
Binomial distribution | |
Chi squared distribution | |
Exponential distribution | 6 |
Gamma distribution | |
Log normal distribution | |
Negative binomial distribution | |
Normal distribution | 0 |
Poisson distribution | |
Student's t distribution |
ZOS
- The syntax is to calculate KURTOSIS in ZOS is
- Parameters are any values to calculate kurtosis.
- For e.g., KURT([-1..-10,20..25..0.5])
Examples
A | B | C | D | E | |
---|---|---|---|---|---|
1 | 14 | 11 | 23 | 54 | 38 |
2 | 6 | 7 | 8 | 9 | 10 |
3 | 1898 | 1987 | 1786 | 1947 | |
4 | 26 | 16 | 12 |
- =KURT(A1:E1) = -0.8704870491886512
- =KURT(A2:E2) = -1.199999999
- =KURT(A3:D3) = 0.8709011137293157
- =KURT(A4:C4) = NAN
Related Videos
See Also
References