When evaluating a multiple regression model, for example when we regress dependent variable Y on two independent variables X1 and X2, a commonly used goodness of fit measure is:

Adjusted-R2

Step-by-step explanation:

When evaluating a multiple regression model, a commonly used goodness of fit is the adjusted-R2. It allows for a comparison of regression models with multiple predictors or independent variables. The addition of independent variables usually causes the model to be more reliable. The adjusted-R2 considers the effect of additional independent variables. It usually adjusts for the number of terms in the model.

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step-by-step explanation:

the ratio of white tiles to blue tiles is 48: 16. the ratio in it's simplest form is 3: 1.

step-by-step explanation:

ratio: take the first number and add a colon next to it, then add the second number after that. make sure the ratio order matches up with the written problem!

simplest form: we can simplify the ratio 48 : 16 by dividing both terms by the greatest common factor (gcf).

the gcf of 48 and 16 is 16.

divide both terms by 16:

48 ÷ 16 = 3

16 ÷ 16 = 1

reducing to simplest form:

48 : 16 = 3 : 1