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= 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.

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What is coefficient of determination?

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.


How is coefficient of determination and coefficient of correlation is related?

coefficient of determination


How would one explain the 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.


What is coefficient variation?

it is da same as coefficient of determination


What is the noun form of determine?

it is determination


What is numerical range of regression coefficient?

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.


Multiple coefficient of determination and a regress ion table?

Adjusted R2


What is the verb from determination?

The verb from 'determination' is 'determine'.


What is the verb for determination?

The verb for determination is "determine".


What does the coefficient of determination explain in regression?

The coefficient, also commonly known as R-square, is used as a guideline to measure the accuracy of the model.


What is the noun form of a verb determine?

The noun form of the verb "determine" is "determination."


What is the coefficient of determination if r 0.45?

The coefficient of determination, denoted as ( R^2 ), is calculated by squaring the correlation coefficient ( r ). If ( r = 0.45 ), then ( R^2 = (0.45)^2 = 0.2025 ). This means that approximately 20.25% of the variance in the dependent variable can be explained by the independent variable in the regression model.

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