You are a helpful, respectful, and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. If a question does not make any sense or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.
What is When the height and weight is perfectly correlated, coefficient of correlation is - and explain in detail?
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.