Difference between revisions of "Manuals/calci/FISHER"

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(Created page with "<div id="6SpaceContent" class="zcontent" align="left"> '''FISHER'''('''n''') '''n'''   is a numeric value for which  the transformation is done. </div> ---- <div...")
 
 
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<div style="font-size:30px">'''FISHER (Number)'''</div><br/>
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*<math>Number</math> is the value to find the Fisher transformation.
 +
**FISHER(), returns the Fisher transformation.
  
'''FISHER'''('''n''')
+
==Description==
 +
*This function gives the value of Fisher Transformation for the given number.
 +
*Fisher Transformation is used  to test the hypothesis of two correlations.
 +
*It is mainly associated with the Pearson Product-Moment Correlation coefficient for bi-variate normal observations.
 +
*In <math>FISHER(Number)</math>, <math>Number</math> is the value which ranges between -1 to +1.
 +
*The transformation is defined by : <math>z=\frac{1}{2} ln(1+\frac{x}{1-x})= arctanh(x)</math>
 +
where <math> ln </math> is the natural logarithm function and <math> arctanh </math> is the Inverse Hyperbolic function.
 +
*This function will give the result as error when:
 +
1.<math>Number</math> is non-numeric
 +
2.<math>Number \le -1</math> or <math>Number \ge 1</math>.
  
'''n'''   is a numeric value for which  the transformation is done.
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==ZOS==
 +
*The syntax is to calculate FISHER in ZOS is <math>FISHER(Number)</math>.
 +
**<math>Number</math> is the value to find the Fisher transformation.
 +
*For e.g.,FISHER(0.1..0.4..0.1)
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{{#ev:youtube|53cqYfgeMzA|280|center|Fisher Transformation}}
  
</div>
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==Examples==
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<div id="1SpaceContent" class="zcontent" align="left">
 
  
It calculates the Fisher transformation at n.
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#FISHER(0.5642) = 0.6389731838284958
 +
#FISHER(0)= 0
 +
#FISHER(-0.3278) = -0.3403614004970268
 +
#FISHER(1) = Infinity
 +
#FISHER(-1) = -Infinity
  
</div>
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==Related Videos==
----
 
<div id="7SpaceContent" class="zcontent" align="left">
 
  
·          For nonnumeric value Fisher shows error.
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{{#ev:youtube|I0SjHVOHztc|280|center|Sampling Distributions}}
  
·          When n is less than or equal to 1or greater than or equal to -1 Fisher displays infinity..
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==See Also==
 +
*[[Manuals/calci/CORREL  | CORREL ]]
 +
*[[Manuals/calci/FISHERINV  | FISHERINV ]]
  
·          The equation for  Fisher transformation is:
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==References==
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[http://en.wikipedia.org/wiki/F-distribution  Fisher Distribution]
  
</div>
 
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<div id="12SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="left">FISHER</div></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>
 
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<div id="4SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Remarks </div></div>
 
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<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="8SpaceContent" class="zcontent" align="left"><font size="3"><font face="Times New Roman">''' <font size="3"><font face="Times New Roman">AVEDEV (N1, N2...)</font></font> <font size="3"><font face="Times New Roman">Where N1, N 2 ...   are positive integers.</font></font> '''</font></font></div>
 
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<div id="5SpaceContent" class="zcontent" align="left">
 
  
<font size="3"><font face="Times New Roman">Let’s see an example in (Column1 Row 1)</font></font>
 
  
<font size="3">FISHER (n)</font>
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*[[Z_API_Functions | List of Main Z Functions]]
  
<font size="3">FISHER (C1R1)</font>
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*[[ Z3 Z3 home ]]
 
 
<font size="3">i.e. =FISHER (.65) is 0.7753</font>
 
 
 
</div>
 
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<div id="9SpaceContent" class="zcontent" align="left">
 
 
 
{| id="TABLE1" class="SpreadSheet blue"
 
|- class="even"
 
| class="    " |
 
| Column1
 
| class="      " | Column2
 
| class="  " | Column3
 
| class="  " | Column4
 
|- class="odd"
 
| class=" " | Row1
 
| class="sshl_f " | .65
 
| class="sshl_f" | 0.775299
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="even"
 
| class="  " | Row2
 
| class="sshl_f" |
 
| class="SelectTD" |
 
<div id="9Space_Handle" class="zhandles" title="Click and Drag to resize CALCI Column/Row/Cell. It is EZ!"></div><div id="9Space_Copy" class="zhandles" title="Click and Drag over to AutoFill other cells."></div><div id="9Space_Drag" class="zhandles" title="Click and Drag to Move/Copy Area.">[[Image:copy-cube.gif]]</div>
 
| class="  " |
 
| class="sshl_f" |
 
|- class="odd"
 
| Row3
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="even"
 
| Row4
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="odd"
 
| class=" " | Row5
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="even"
 
| Row6
 
| class="sshl_f  " |
 
| class="sshl_f   " |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|}
 
 
 
<div align="left">[[Image:calci1.gif]]</div></div>
 
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Latest revision as of 17:01, 7 August 2018

FISHER (Number)


  • is the value to find the Fisher transformation.
    • FISHER(), returns the Fisher transformation.

Description

  • This function gives the value of Fisher Transformation for the given number.
  • Fisher Transformation is used to test the hypothesis of two correlations.
  • It is mainly associated with the Pearson Product-Moment Correlation coefficient for bi-variate normal observations.
  • In , is the value which ranges between -1 to +1.
  • The transformation is defined by :

where is the natural logarithm function and is the Inverse Hyperbolic function.

  • This function will give the result as error when:
1. is non-numeric
2. or .

ZOS

  • The syntax is to calculate FISHER in ZOS is .
    • is the value to find the Fisher transformation.
  • For e.g.,FISHER(0.1..0.4..0.1)
Fisher Transformation

Examples

  1. FISHER(0.5642) = 0.6389731838284958
  2. FISHER(0)= 0
  3. FISHER(-0.3278) = -0.3403614004970268
  4. FISHER(1) = Infinity
  5. FISHER(-1) = -Infinity

Related Videos

Sampling Distributions

See Also

References

Fisher Distribution