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What is coefficient of determination?

Updated: 4/28/2022
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9y ago

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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.

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15y ago
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Q: What is coefficient of determination?
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Related questions

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

coefficient of determination


What is coefficient variation?

it is da same as coefficient of determination


How do you determine coefficient of determination in excel?

= 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.


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.


Multiple coefficient of determination and a regress ion table?

Adjusted R2


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.


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 are the uses of emf measurements?

1- Determination of activity coefficient . 2-determination of of composition of complex ion. 3-Potentiometric titrations.


Cause and effect relationships cannot be determined using the coefficient of determination?

True


The percent variance in Y explained by variability in X is called the?

r2, the coefficient of determination


What is the difference between the coefficient of simple determination and that of multiple determination?

The coefficient of simple determination tells the proportion of variance in one variable that can be accounted for (or explained) by variance in another variable. The coefficient of multiple determination is the Proportion of variance X and Y share with Z; or proportion of variance in Z that can be explained by X & Y.


Can A regression equation have a negative coefficient of correlation and a negative coefficient of determination?

It's not quite possible for the coefficient of determination to be negative at all, because of its definition as r2 (coefficient of correlation squared). The coefficient of determination is useful since tells us how accurate the regression line's predictions will be but it cannot tell us which direction the line is going since it will always be a positive quantity even if the correlation is negative. On the other hand, r (the coefficient of correlation) gives the strength and direction of the correlation but says nothing about the regression line equation. Both r and r2 are found similarly but they are typically used to tell us different things.