Difference between revisions of "Manuals/calci/KURT"

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*Kurtosis is defined by:
 
*Kurtosis is defined by:
 
*Kurtosis=:
 
*Kurtosis=:
<math>{\frac{n(n+1)}{(n-1)(n-2)(n-3)}*\sum[(xi-\bar{x})/s]^4}-3(n-1)^2/(n-2)(n-3)</math>, where <math>s</math> is the sample standard deviation.x(bar) is the arithmetic mean.
+
<math>{\frac{n(n+1)}{(n-1)(n-2)(n-3)}*\frac{\sum{\frac{(xi-\bar{x})^4}{s}}\frac{-3(n-1)^2}{(n-2)(n-3)}</math>, where <math>s</math> is the sample standard deviation.x(bar) is the arithmetic mean.
 
*In this function arguments may be any type like numbers,names,arrays or references that contain numbers.
 
*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.
 
*We can give logical values and text references also directly.
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*This function will return the result as error when  
 
*This function will return the result as error when  
 
#Any one of the argument is non-numeric.
 
#Any one of the argument is non-numeric.
#suppose the number of data points are less than four or the standard deviation of the sampleis zero
+
#suppose the number of data points are less than four or the standard deviation of the sample is zero
 
#The referred arguments could not convert
 
#The referred arguments could not convert
 
  in to numbers.
 
  in to numbers.

Revision as of 02:12, 13 December 2013

KURT(n1,n2,…)


  • , are values to calculate kurtosis.

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=:

Failed to parse (syntax error): {\displaystyle {\frac{n(n+1)}{(n-1)(n-2)(n-3)}*\frac{\sum{\frac{(xi-\bar{x})^4}{s}}\frac{-3(n-1)^2}{(n-2)(n-3)}} , where is the sample standard deviation.x(bar) 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.

Examples

1.DATA 14 11 23 54 38 KURT(C1:C5)=-0.8704870492 2. DATA={6,7,8,9,10} KURT(A1:A5)=-1.199999999 3.DATA={1898,1987,1786,1947} KURT(B1:B4)=0.870901113729 4.DATA={26,16,12} KURT(D1:D3)=NAN

See Also

References

Correlation