### RESEARCH METHODOLOGY

 Question [CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
What is the difference between coefficients r and r2?
 A R represents correlation and R2 represents probability B R represents variance and R2 represents correlation C R represents correlation and R2 represents variance D R represents probability and R2 represents variance
Explanation:

Detailed explanation-1: -Whereas correlation explains the strength of the relationship between an independent and dependent variable, R-squared explains to what extent the variance of one variable explains the variance of the second variable.

Detailed explanation-2: -The Pearson correlation coefficient (r) is used to identify patterns in things whereas the coefficient of determination (R²) is used to identify the strength of a model.

Detailed explanation-3: -The R-squared value, denoted by R 2, is the square of the correlation. It measures the proportion of variation in the dependent variable that can be attributed to the independent variable. The R-squared value R 2 is always between 0 and 1 inclusive.

Detailed explanation-4: -The R2 tells us the percentage of variance in the outcome that is explained by the predictor variables (i.e., the information we do know). A perfect R2 of 1.00 means that our predictor variables explain 100% of the variance in the outcome we are trying to predict.

Detailed explanation-5: -The coefficient of determination is often written as R2, which is pronounced as “r squared.” For simple linear regressions, a lowercase r is usually used instead (r2).

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