in multiple linear regression, what does R2 value ( coefficient of determination
ID: 3269155 • Letter: I
Question
in multiple linear regression, what does R2 value ( coefficient of determination) indicate? a. the correlation between two varaibles and their predicted value b. the test significance or R when the degree of freedom equals zero c. the residual degrees of freedom after computing the squared variances d. the propoortion of variance in the outcome variable that is explained by the predictor variable
according to the unstandardized multiple linear regression equation, the best prdictio of the outcome variable y equals? a. the interpret plus the sum of the products by multiplying each predictor variable (x) bycorresponding regression coefficientfor all predictors b.the sum of all the variables (x) each multipled by their regression coefficientplus error c.the intercept minus the sum of all the predictors variables (x) each multipliedby their regression coefficient d. the intercept minus the sum of all the predictor varaibles (x), each divided by their regression coefficient
An unstandardized coefficient associate with a predictor variable in a multiple linear regression equation is: a. the same as when a simple linear regression is fit with corresponding independent varaible (predictor) b. less interpretable an an index of a predictor relative importance when it is standardized c. not suitable for inference based on a confidence intervel d. the amount of change in dependent variable associated with a unit change in prdictor variable when the effetc of other predictors are taken into account
Explanation / Answer
* In multiple linear regression , R squared indicate the proporation of variance in the outcome variable that is explained by the predictor variable .
** answer is a) the intercept plus the sum of products by multiplying each predictor variable x by corresponding regression coefficient for all predictors
*** Answer is (a )
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