Difference between revisions of "Manuals/calci/PEARSON"

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<div style="font-size:30px">'''PEARSON (ar1,ar2)'''</div><br/>
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<div style="font-size:30px">'''PEARSON (Array1,Array2)'''</div><br/>
*<math>ar_1</math> is the array of independent values  
+
*<math>Array1</math> is the array of independent values  
*<math>ar_2</math> is the array of dependent values.
+
*<math>Array2</math> is the array of dependent values.
 +
**PEARSON(),returns the Pearson product moment correlation coefficient.
  
 
==Description==
 
==Description==
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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(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.  
+
*In  <math>PEARSON(Array1,Array2)</math>, the value of <math>Array1</math> and <math>Array2</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> ar_1 </math> and <math> ar_2 </math>.
+
*This function will return the result as error when the number of values are different for <math> Array1 </math> and <math> Array2 </math>.
  
 
==Examples==
 
==Examples==

Latest revision as of 16:01, 8 August 2018

PEARSON (Array1,Array2)


  • is the array of independent values
  • is the array of dependent values.
    • PEARSON(),returns the Pearson product moment correlation coefficient.

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) = 0.034204238054579846

3.

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

Related Videos

PEARSON

See Also

References

Pearson