Correlation Coefficient is the ratios that measure the degree of two random variables vary or correlate each other. For example if the coefficient of correlation is 95% it implies that there is 95% relationship between the variables. In other words the two variables are said to be correlated if they tend to move simultaneously or vary in some direction.
If with the increase (or decrease) of one variable the other variable also increase (or decrease) the correlation is called positive correlation and if with the increase in one variable result in decrease in other variable the correlation is called as negative or inverse because they are both moving in opposite directions
Examples of positive and negative correlations
With increase in temperature the length of iron rod also increase
With the increase in population the decrease in food supply
Coefficient of correlation is represented by the "r" which ranges from -1 to +1. -1 indicates negative correlation +1 represent the positive relationship and 0 shows that no relationship between the two variables exist.
It's worth noting that:
Correlation doesn't take the dependency of two variables (as in the case of regression). In other words in correlation we are interested in determining the degree of relationship between random variables not dependant and independent variable