Difference between revisions of "Manuals/calci/PEARSON"
Jump to navigation
Jump to search
Line 1: | Line 1: | ||
<div style="font-size:30px">'''PEARSON (ar1,ar2)'''</div><br/> | <div style="font-size:30px">'''PEARSON (ar1,ar2)'''</div><br/> | ||
− | *<math> | + | *<math>ar_1</math> is the array of independent values |
− | *<math> | + | *<math>ar_2</math> is the array of dependent values. |
==Description== | ==Description== | ||
− | *This function gives the Pearson | + | *This function gives the Pearson Product-Moment Correlation Coefficient. |
*It is denoted by PPMC, which shows the linear relationship between two variables. | *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 . | *It is a measure of the strength of a linear association between two variables . | ||
*The two variables <math> X </math> and <math> Y </math>, giving a value between +1 and −1 inclusive. | *The two variables <math> X </math> and <math> Y </math>, giving a value between +1 and −1 inclusive. | ||
− | *Here +1 indicates the perfect positive correlation, 0 indicates no correlation | + | *Here |
+ | +1 indicates the perfect positive correlation, | ||
+ | 0 indicates no 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> |
Revision as of 02:00, 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
A | B | C | |
---|---|---|---|
1 | 5 | 9 | 10 |
2 | 8 | 12 | 15 |
=PEARSON(A1:C1,A2:C2) = 0.968619605
2.
A | B | C | D | |
---|---|---|---|---|
1 | 17 | 0 | 19 | 25 |
2 | 10 | 11 | 7 | 13 |
=PEARSON(A1:D1,A2:D2) = -0.759206026
3.
A | B | C | |
---|---|---|---|
1 | 1 | 2 | 3 |
2 | 4 | 5 |
=PEARSON(A1:C1,A2:B2) = NAN