Difference between revisions of "Manuals/calci/KURT"

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(Created page with "<div id="6SpaceContent" class="zcontent" align="left"> '''KURT'''(N'''1''',N2,...) '''Where N1,N2,.... '''are the arguments to calculate the kurtosis. </div> ---- <...")
 
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<div style="font-size:30px">'''KURT(n1,n2,…)'''</div><br/>
 +
*<math>n1</math>,<math>n2</math> are values to calculate kurtosis.
 +
==Description==
 +
*This function gives the value of kurtosis of a given set.
 +
*Kurtosis is  the peakedness or flatness of the graph of a frequency distribution 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,possion distribution, Laplace distribution.
 +
*Example for negative kurtosis(platykurtosis) is Bernoulli distribution, Uniform distribution.
 +
*Kurtosis has no units.
 +
*Kurtosis is defined by:
 +
*kurtosis={n(n+1)/(n-1)(n-2)(n-3)*summation[(xi-x(bar)/s]^4}-3(n-1)^2/(n-2)(n-3), wher s is the sample standard deviation.x(bar) is the arithmetic mean.
 +
*In this function argumentsmay 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
 +
#Any one of the argument is nonnumeric.
 +
#suppose the number of data points are less than four or the standard deviation of the sampleis zero
 +
#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==
 +
*[[Manuals/calci/SKEW  | SKEW ]]
 +
*[[Manuals/calci/STDEV  | STDEV ]]
 +
*[[Manuals/calci/STDEVP  | STDEVP ]]
  
'''KURT'''(N'''1''',N2,...)
+
==References==
 
+
[http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient Correlation]
'''Where N1,N2,.... '''are the arguments to calculate the kurtosis.
 
 
 
</div>
 
----
 
<div id="1SpaceContent" class="zcontent" align="left">
 
 
 
This function calculates the relative peakedness or flatness of a distribution compared with the normal distribution.
 
 
 
</div>
 
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<div id="7SpaceContent" class="zcontent" align="left">
 
 
 
·          Arguments can be numbers or names, arrays, or references.
 
 
 
·          Logical values and text representations of numbers are calculated.
 
 
 
·        KURT shows the error value, when there are fewer than four data points, or the SD of the sample equals zero.
 
 
 
Formulas:-
 
 
 
·          Kurtosis is defined as:
 
 
 
where s is the sample standard deviation.
 
 
 
</div>
 
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<div id="12SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="left">
 
 
 
KURT
 
 
 
</div></div>
 
----
 
<div id="8SpaceContent" class="zcontent" align="left">
 
 
 
{| class="MsoNormalTable" cellspacing="3"
 
| valign="top" |
 
<font face="Arial">Lets see an example,</font>
 
 
 
<font face="Arial">KURT(N1,N2,....)</font>
 
 
 
<font face="Arial"></font>
 
 
 
'''<font face="Arial">B</font>'''
 
 
 
<font face="Arial"></font>8
 
 
 
9
 
 
 
10
 
 
 
4
 
 
 
5
 
 
 
3
 
 
 
10
 
 
 
<font face="Arial"><nowiki>=KURT(B2:B8) is -2.0947</nowiki></font>
 
 
 
<font face="Arial"></font>
 
|}
 
 
 
</div>
 
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<div id="10SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Syntax </div><div class="ZEditBox"><center></center></div></div>
 
----
 
<div id="4SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Remarks </div></div>
 
----
 
<div id="3SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Examples </div></div>
 
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<div id="11SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Description </div></div>
 
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<div id="2SpaceContent" class="zcontent" align="left">
 
 
 
{| id="TABLE3" class="SpreadSheet blue"
 
|- class="even"
 
| class="    " |
 
| class="  " | Column1
 
| class="  " | Column2
 
| class="  " | Column3
 
| class="  " | Column4
 
|- class="odd"
 
| class=" " | Row1
 
| class="sshl_f " | 8
 
| class="sshl_f" | -2.094675
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="even"
 
| class=" " | Row2
 
| class="sshl_f  " | 9
 
| class="SelectTD" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="odd"
 
| Row3
 
| class="sshl_f  " | 10
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="even"
 
| Row4
 
| class="sshl_f  " | 4
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="odd"
 
| class=" " | Row5
 
| class="sshl_f  " | 5
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="even"
 
| class="sshl_f" | Row6
 
| class="sshl_f  " | 3
 
| class="sshl_f  " |
 
| class="sshl_f  " |
 
| class="sshl_f  " |
 
|- class="odd"
 
| class="sshl_f" | Row7
 
| class="sshl_f " | 10
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|}
 
 
 
<div align="left">[[Image:calci1.gif]]</div></div>
 
----
 

Revision as of 01:39, 12 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 peakedness or flatness of the graph of a frequency distribution 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,possion distribution, Laplace distribution.
  • Example for negative kurtosis(platykurtosis) is Bernoulli distribution, Uniform distribution.
  • Kurtosis has no units.
  • Kurtosis is defined by:
  • kurtosis={n(n+1)/(n-1)(n-2)(n-3)*summation[(xi-x(bar)/s]^4}-3(n-1)^2/(n-2)(n-3), wher s is the sample standard deviation.x(bar) is the arithmetic mean.
  • In this function argumentsmay 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 nonnumeric.
  2. suppose the number of data points are less than four or the standard deviation of the sampleis 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