Difference between revisions of "Manuals/calci/PEARSON"
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*Here +1 indicates the perfect positive correlation, 0 indicates no correlation and -1 indicates the perfect negative correlation. | *Here +1 indicates the perfect positive correlation, 0 indicates no correlation and -1 indicates the perfect negative correlation. | ||
*The formula for PPMC,r is defined by: | *The formula for PPMC,r 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} and \bar{y} | + | where <math>\bar{x} and \bar{y} </math> are Average of the two Samples x and y. |
*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(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. | ||
*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. | ||
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==Examples== | ==Examples== | ||
− | + | *1.Array1 Array2 | |
5 8 | 5 8 | ||
9 12 | 9 12 | ||
10 15 | 10 15 | ||
PEARSON(B1:B3,C1:C3)=0.968619605 | PEARSON(B1:B3,C1:C3)=0.968619605 | ||
− | + | *2.Array1 Array2 | |
17 10 | 17 10 | ||
0 11 | 0 11 | ||
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25 13 | 25 13 | ||
PEARSON(D1:D4,E1:E4)=-0.759206026 | PEARSON(D1:D4,E1:E4)=-0.759206026 | ||
− | + | *3.Array1 Array2 | |
1 4 | 1 4 | ||
2 5 | 2 5 | ||
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==References== | ==References== | ||
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Revision as of 23:16, 5 January 2014
PEARSON (ar1,ar2)
- is the array of independent values and is the array of dependent values.
Description
- This function gives the Pearson productmoment correlaton 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 X and Y, giving a value between +1 and −1 inclusive.
- Here +1 indicates the perfect positive correlation, 0 indicates no correlation and -1 indicates the perfect negative correlation.
- The formula for PPMC,r is defined by:
where are Average of the two Samples x and y.
- 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 ar1 and ar2.
Examples
- 1.Array1 Array2
5 8 9 12 10 15 PEARSON(B1:B3,C1:C3)=0.968619605
- 2.Array1 Array2
17 10
0 11 19 7 25 13 PEARSON(D1:D4,E1:E4)=-0.759206026
- 3.Array1 Array2
1 4 2 5 3 PEARSON(A1:A3,B1:B2)=NAN