Difference between revisions of "Manuals/calci/PEARSON"

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   0 indicates no correlation  
 
   0 indicates no correlation  
 
  -1 indicates the perfect negative correlation.
 
  -1 indicates the perfect negative correlation.
*The formula for PPMC,<math> r </math> is defined by:
+
*The formula for PPMC, <math> r </math> is defined by:
 
<math> r= \frac{ \Sigma(x-\bar{x})(y-\bar{y})}{\sqrt {\Sigma(x-\bar{x})^2(y-\bar{y})^2}}</math>     
 
<math> r= \frac{ \Sigma(x-\bar{x})(y-\bar{y})}{\sqrt {\Sigma(x-\bar{x})^2(y-\bar{y})^2}}</math>     
  
 
where <math> \bar{x}</math>  and  <math>\bar{y} </math>  are Average of the two Samples  <math>x </math> and  <math>y </math>.
 
where <math> \bar{x}</math>  and  <math>\bar{y} </math>  are Average of the two Samples  <math>x </math> and  <math>y </math>.
*In  <math>PEARSON(ar1,ar2)</math>, the value of <math> ar1</math> and <math> ar2</math> must be either numbers or names, array,constants or references that contain numbers.  
+
*In  <math>PEARSON(ar_1,ar_2)</math>, the value of <math> ar_1</math> and <math> ar_2</math> must be either numbers or names, array,constants or references that contain numbers.  
*Suppose the array contains text,logicl values or empty cells, like that values are not considered.
+
*Suppose the array contains text, logicl values or empty cells, like that values are not considered.
*This function will return the result as error when the number of values are different for <math> ar1 </math> and <math> ar2 </math>.
+
*This function will return the result as error when the number of values are different for <math> ar_1 </math> and <math> ar_2 </math>.
  
 
==Examples==
 
==Examples==

Revision as of 02:01, 22 January 2014

PEARSON (ar1,ar2)


  • is the array of independent values
  • is the array of dependent values.

Description

  • This function gives the Pearson Product-Moment Correlation Coefficient.
  • It is denoted by PPMC, which shows the linear relationship between two variables.
  • It is a measure of the strength of a linear association between two variables .
  • The two variables and , giving a value between +1 and −1 inclusive.
  • Here
+1 indicates the perfect positive correlation,
 0 indicates no correlation 
-1 indicates the perfect negative correlation.
  • The formula for PPMC, is defined by:

where and are Average of the two Samples and .

  • In , the value of and must be either numbers or names, array,constants or references that contain numbers.
  • Suppose the array contains text, logicl values or empty cells, like that values are not considered.
  • This function will return the result as error when the number of values are different for and .

Examples

Spreadsheet
A B C
1 5 9 10
2 8 12 15
=PEARSON(A1:C1,A2:C2) = 0.968619605

2.

Spreadsheet
A B C D
1 17 0 19 25
2 10 11 7 13
=PEARSON(A1:D1,A2:D2) = -0.759206026

3.

Spreadsheet
A B C
1 1 2 3
2 4 5
=PEARSON(A1:C1,A2:B2) = NAN

See Also

References

Pearson