Reference no: EM13154870

11. TRUE/FALSE: One formula for the Root Mean Square Error of a regression line is simply (R2) * (SD of y). 
True
False

13.
What are the correct ranges of the correlation coefficient r and the multiple correlation coefficient R?
-1 < r < 1
-1 < R < 1

-1 < r < 1
0 < R < 1

0 < r < 1
-1 < R < 1

0 < r < 1
0 < R < 1

None of these is correct
14.
In a bivariate linear regression, if the null hypothesis that B1 = 0 is rejected, which quantity in the accompanying ANOVA table will be larger?
MSV Residual
MSV Regression
They would be roughly equivalent

15.
For a bivariate linear regression, will a test of the hypothesis H0: B0 = 0 provide evdience that using the regression equation to make predictions will result in smaller errors than using the mean of Y as the best estimate?
Yes
No

16.
Edna wishes to make a Type I error no more than 5% of the time. A coefficient B has an associated p-value of 0.01 in one of her regression tables. Should she reject the null hypothesis that B = 0?
Yes
No
1) Which is true for Anscombe datasets?
a)That one should always graph data before running a regression
b) that one should requesting many residual diagnostics after running a regression
c) that regression as a general technique is far superior to correlation alone
d) that multivariate regression has additional assumptions that bivariate regression does not
e) none of these statements is demonstrated by the Anscombe datasets

Which answer best completes the sentence: When interpreting a standardized partial regression coefficient Bi, we state that an increase in _____________ of 1 unit results in a change in ___________ of Bi units in our prediction. 


raw units of X, raw units of Y
raw units of X, standard deviations of Y
standard deviations of X, standard deviations of Y
raw units of Y, raw units of X
standard deviations of Y, standard deviations of X

4.
How many residuals (estimate - actual) are estimated for each observation [Y,X1,X2] in a multivariate regression with two predictor variables (X1 and X2)?

For a multivariate regression there are no residuals
One residual for each observation
Two residuals for each observation
Three residuals for each observation
None of these answers is correct

5.
TRUE/FALSE: Multivariate regression can be used both for predicting outcomes and for investigating the causes of outcomes. 
True
False