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1) Suppose we use simple linear regression to analyze the relationship between a

ID: 3365961 • 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, thanks!

Explanation / Answer

Ans:

1)

As,we reject H0: = 0 in favor of HA: 0,it means that there exist linear relationship bwteen two variables.

So,Option b is correct.

The observed linear relationship is provides a better fit than a horizontal line.

2)Option a is correct

The Pearson correlation coefficient .

(measures the strength and direction of association of linear relationship between two variables.)

In order to measure the strength of a linear relationship between two quantitative variables we use correlation. Correlation is the measure of the strength of a linear relationship.