For a Simple Linear Regression Model, Significance of Regression Is

Multiple Choice

For a simple linear regression model, significance of regression is:

A) a measure of how well the regression line fits the data.
B) a hypothesis test of whether the true regression coefficient ß1 is zero.
C) a statistic that modifies the value of R2 by incorporating the sample size and the number of explanatory variables in the model.
D) the variability of the observed Y-values from the predicted values.