Respuesta :
Answer:
Correlation coefficients range from _-1__ to _+1__. A correlation coefficient suggest the _strength__ and _direction__ of the relationship between variables. A correlation of _+1__ indicates a perfect positive relationship; _-1__ indicates a perfect negative relationship; and _0__ indicates that there is no linear correlation between the variables.
Step-by-step explanation:
Correlation Coefficient(r) shows the direction and strength of relationship between two variables.
The formula used to calculate correlation is:
[tex]Correlation(r) = \frac{Cov(x, y)}{\sigma_{x}\sigma_{y}}= \frac{E(x-\mu_{x})(y-\mu_{y})}{\sigma_{x}\sigma_{y}}[/tex]
where, Cov(x,y) = Covariance of x and y
[tex]\mu_{x} [/tex] = mean of x
[tex]\mu_{y} [/tex] = mean of y
[tex]\sigma_{x} [/tex] = standard deviation of x
[tex]\sigma_{y} [/tex] = standard deviation of y
and, E = Expectation.
The correlation coefficient lies between -1 to +1.
As the increase in the value of one variable also increases the value of other variables is called positive correlation. Also, the value of positive correlation lies between 0 to 1.
And decrease in the value of one variable, increases the value of other variables is called negative correlation. Also, the value of negative correlation lies between -1 to 0.
