Types of Correlattion
1.Positive correlation A positive correlation is a correlation in the same direction.
2. Negative Correlation
A negative correlation is a correlation in the opposite direction.
3. Partial Correlation
The correlation is partial if we study the relationship between two variables keeping all other variables constant.
Example: The Relationship between yield and rainfall at a constant
temperature is partial correlation.
4. Linear Correlation
When the change in one variable results in the constant change in the other variable, we say the correlation is linear. When there is a
linear correlation, the points plotted will be in a straight line
Example: Consider the variables with the following values.
X :
1 2
3 4
50 Y: 2
4 6
8 10
Here, there is a linear relationship between the variables.
There is a ratio 1:2 at all points. Also, if we plot them they will be in a straight line
Correlation are of three types:
Positive Correlation
Negative Correlation
No correlation
In correlation, when values of one variable increase with the increase in another variable, it is supposed to be a positive
correlation. On the other hand, if the values of one variable decrease with the decrease in another variable, then it would be
a negative correlation. There might be the case when there is no change in a variable with any change in another variable. In this
case, it is defined as no correlation between the two.
Correlation Symbol Symbol of correlation = rr
Correlation Formula
The formula for correlation is as follows,
Correlation r = N∑XY−∑X∑Y[N∑X2−∑X2][N∑Y2− ∑Y2]√N∑XY−∑X∑Y[N∑X2−∑X2][N∑Y2−∑Y2]
Where, xx and yy are the variables.
bb = the slope of the regression line is also called as the regression coefficient
aa = intercept point of the regression line which is in the y-axis.
NN = Number of values or elements
XX = First Score
YY = Second Score
∑XY∑XY = Sum of the product of the first and Second Scores ∑X∑X = Sum of First Scores
∑Y∑Y = Sum of Second Scores ∑X2∑X2 = Sum of square first scores.
∑Y2∑Y2 = Sum of square second scores.
r = n∑xy−∑x∑yn∑x2−∑x2√n∑y2−∑y2√n∑xy−∑x∑yn∑x2−
∑x2n∑y2−∑y2
1. Positive Correlation
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