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Correlation 1

The document discusses correlation and the different types of correlation between two variables. Correlation is the degree of relationship between variables, and can be positive, negative, or zero depending on whether the variables change in the same direction or opposite directions. The Karl Pearson coefficient of correlation numerically measures the linear relationship between variables.

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47 views9 pages

Correlation 1

The document discusses correlation and the different types of correlation between two variables. Correlation is the degree of relationship between variables, and can be positive, negative, or zero depending on whether the variables change in the same direction or opposite directions. The Karl Pearson coefficient of correlation numerically measures the linear relationship between variables.

Uploaded by

akinrav
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as PDF, TXT or read online on Scribd
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 Basically correlation is the degree of relationship

between two or more variables.

 If Change the value one variable, effect the value of


another variable then we can say they are correlated to
each other.
Correlation coefficient between two random variables X
and Y, usually denoted by 𝑟 𝑋, 𝑌 or simply 𝑟𝑋𝑌 . It is a
numerical measure of linear relationship between them
and is defined as
𝐶𝑜𝑣(𝑋, 𝑌)
𝑟 𝑋, 𝑌 =
σ𝑋 σ𝑌
* −1 ≤ 𝑟 ≤ 1
*This formula is given by Karl Pearson that’s why it is
called as Karl Pearson coefficient of correlation.
Basically there are three types of correlation

 Positive correlation
 Negative correlation
 Zero correlation
 If we increase the value of one variable then the value
of another variable is also increased.

 If we decrease the value of one variable then the value


of another variable goes to decrease.

It means, if the variables goes to the same direction with


the change of their values then they have positive
correlation
 If we increase the value of one variable then the value
of another variable goes to decrease.

 If we decrease the value of one variable then the value


of another variable goes to increase.

It means, if the variables goes to the different directions


with the change of their values then they have negative
correlation.
If the change in the value of one variable does not effect the
value of another variable then we can say they have a zero
correlation or no correlation.
 𝑟 = −1 Perfect Negative Correlation
 −1 < 𝑟 < 0 Negative Correlation
 𝑟=0 Zero Correlation
 0 <𝑟 <1 Positive Correlation
 𝑟=1 Perfect Positive Correlation

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