When the height and weight is perfectly correlated, coefficient of correlation is -

Ans. is 'a' i.e., +1 o If height and weight are perfectly correlated then increase in height will cause propoionate increase weight and it is represented by correlation cofficient + 1. Also know: o Multiplication correlation coefficient: It is used for calculation between one variable (dependent)) and the combination of two or more variable (Independent) o Coefficient of determination (r2) The correlation coefficient (r) is frequency used descriptive measure to represent the degree of linear association between two random variables X and Y. The coefficient of determination (r2) is another measure that is often used to describe the degree of linear association between X and Y. Coefficient of determination is the percentage of variation in a variable (dependent) that is explained by one ore more others (independents) Coefficient of determination (r2) = [Correlation coefficient Of It interprets the value of coefficient of correlation between two variable. For example, if the value of r= 0.9, r2 will be 0.81 and this would mean that 81% of variation in the dependent variable has been explained by the independent variable. Value of this coefficient ranges from 0 to I Unlike correlation coefficient, the coefficient of determination does not assume any negative value, i.e. value of r2 is always ---> 0 5_ r2 . 1. I-2 is generally obtained in a regression setup. It can be used to measure the strength of a simple linear regression as well at the strength of a multiple regression relationship. In multiple regression, the coefficient of determination (r2) is also referred to as the multiple correlation coefficient.