= CORREL(x values,y values)
***clarification****
CORREL gives you the correlation coefficient (r), which is different than the coefficient of determination (R2) outside of simple linear regression situations.
The coefficient of determination R2 is the square of the correlation coefficient. It is used generally to determine the goodness of fit of a model. See: http://en.wikipedia.org/wiki/Coefficient_of_determination for more details.
coefficient of determination
it is da same as coefficient of determination
ɪf the regresion coefficient is the coefficient of determination, then it's range is between 0 or 1. ɪf the regression coefficient is the correaltion coefficient (which i think it is) the it must lie between -1 or 1.
The coefficient, also commonly known as R-square, is used as a guideline to measure the accuracy of the model.
The coefficient of determination R2 is the square of the correlation coefficient. It is used generally to determine the goodness of fit of a model. See: http://en.wikipedia.org/wiki/Coefficient_of_determination for more details.
coefficient of determination
The coefficient of determination, is when someone tries to predict the outcome of the testing of a hypothesis, or their guess at to what will happen. It helps determine how well outcomes are determined beforehand.
it is da same as coefficient of determination
The noun form of "determine" is "determination."
The verb for determination is "determine".
The verb from 'determination' is 'determine'.
Adjusted R2
The noun form of the verb "determine" is "determination."
ɪf the regresion coefficient is the coefficient of determination, then it's range is between 0 or 1. ɪf the regression coefficient is the correaltion coefficient (which i think it is) the it must lie between -1 or 1.
The coefficient, also commonly known as R-square, is used as a guideline to measure the accuracy of the model.
True