1) Suppose we use simple linear regression to analyze the relationship between a
ID: 3365912 • Letter: 1
Question
1) Suppose we use simple linear regression to analyze the relationship between a response variable Y and an explanatory variable X. If we reject H0: = 0 in favor of HA: 0, what can we conclude?
a) A linear relationship between X and Y is the best model.
b) The observed linear relationship is provides a better fit than a horizontal line.
c) Both (a) and (b).
d) Neither (a) nor (b).
2) Which of the following measures the magnitude of the linear association between X and Y:
a) The Pearson correlation coefficient .
b) The slope 1 of the regression line Y = 0 + 1X.
c) Both (a) and (b).
d) Neither (a) nor (b).
Please answer both questions, I will be sure to give you a thumb up!
Explanation / Answer
1. d) Neither a) nor b) Because by accepting beta=0 we can only say that the coefficient of the variable is significant that mean it has some effect in explaining Y but we can't conclude anything about the fit of the model just by acceptance of beta=0.
2. a) Pearson correleation coefficient as it measures the linear association between X and Y. the regression coefficient tell you with one unit increment of X how the Y will change.
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