Difference between revisions of "Manuals/calci/CORREL"

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*For example, test average and study time are related; those who spending more time to study will get high marks and Average will go down for those who spend less time for studies.
 
*For example, test average and study time are related; those who spending more time to study will get high marks and Average will go down for those who spend less time for studies.
 
*There are  different correlation techniques to measure the Degree of Correlation.  
 
*There are  different correlation techniques to measure the Degree of Correlation.  
*The most common of these is the Pearson Correlation Coefficient  denoted by r  xy.
+
*The most common of these is the Pearson Correlation Coefficient  denoted by <math>r_xy</math>.
 
*The main result of a correlation is called the Correlation Coefficient(<math>r</math>)which  ranges from -1 to +1.  
 
*The main result of a correlation is called the Correlation Coefficient(<math>r</math>)which  ranges from -1 to +1.  
 
*The <math>r</math> value is positive i.e +1  when the two set values increase together then it is the perfect Positive Correlation.
 
*The <math>r</math> value is positive i.e +1  when the two set values increase together then it is the perfect Positive Correlation.

Revision as of 00:31, 10 December 2013

CORREL(ar1,ar2)


  • and are the set of values.

Description

  • This function gives the correlation coefficient of the 1st set() of values and 2nd set() of values.
  • Correlation is a statistical technique which shows the relation of strongly paired variables.
  • For example, test average and study time are related; those who spending more time to study will get high marks and Average will go down for those who spend less time for studies.
  • There are different correlation techniques to measure the Degree of Correlation.
  • The most common of these is the Pearson Correlation Coefficient denoted by .
  • The main result of a correlation is called the Correlation Coefficient()which ranges from -1 to +1.
  • The value is positive i.e +1 when the two set values increase together then it is the perfect Positive Correlation.
  • The value is negative i.e. (-1) when one value decreases as the other increases then it is called Negative Correlation.
  • Suppose the value is 0 then there is no correlation (the values don't seem linked at all).
  • If we have a series of measurements of and written as and where then the Sample Correlation Coefficient is:

  • and are the sample means of and .
  • This function will give the result as error when
1. and  are non-numeric or different number of data points.
2. or  is empty
3.The denominator value is zero.
  • Suppose and contains any text, logical values, or empty cells, like that values are ignored.

Examples

  1. 1. Find the correlation coefficients for X and Y values are given below :X={1,2,3,4,5}; Y={11,22,34,43,56}

CORREL(A4:A8,B4:B8)=0.99890610723867

  1. The following table gives the math scores and times taken to run 100 m for 10 friends:SCORE(X)={52,25,35,90,76,40}; TIME TAKEN(Y)={11.3,12.9,11.9,10.2,11.1,12.5}CORREL(A5:A10,B5:B10)= -0.93626409417769
  2. Find the correlation coefficients for X and Y values are given below :X={-4,11,34,87};Y={9,2,59,24} CORREL(A1:A4,B1:B4)=0.353184665607273

See Also


References

Bessel Function