Question

Following is a simple linear regression model: yi = a + bxi + ei The following results were obtained from some statistical software. R^2 = 0.523 syx (regression standard error) = 3.028 n (total observations) = 41 Significance level = 0.05 = 5% Variable Parameter Estimate Std. Err. of Parameter Est. Intercept 0.519 0.132 Slope of X -0.707 0.239 Note: For all the calculated numbers, keep three decimals. Write the fitted model (5 points). Make a prediction using the fitted model for y when x = 1.888 (5 points) 3. The intercept of the least-squares regression line is (5 points): 4. Suppose we want to test the hypotheses for the slope: H0: b = 0, H1: b ≠ 0 The value of the t statistic for this test is (10 points):

          Following is a simple linear regression model:
yi = a + bxi + ei

The following results were obtained from some statistical software.
R^2 = 0.523
syx (regression standard error) = 3.028
n (total observations) = 41
Significance level = 0.05 = 5%

Variable
Parameter Estimate
Std. Err. of Parameter Est.
Intercept
0.519
0.132
Slope of X
-0.707
0.239

Note: For all the calculated numbers, keep three decimals.

Write the fitted model (5 points).
Make a prediction using the fitted model for y when x = 1.888 (5 points)

3. The intercept of the least-squares regression line is (5 points):

4. Suppose we want to test the hypotheses for the slope:
H0: b = 0,
H1: b ≠ 0
The value of the t statistic for this test is (10 points):

Added by Tammy M.

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