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3. Given the linear regression equation: y = 1.6 + 3.5x1 – 7.9x2 + 2.0x3 a....

3. Given the linear regression equation: y = 1.6 + 3.5x1 – 7.9x2 + 2.0x3

a. Which variable is the response variable? How many explanatory variables are there?

b. If x1 = 2, x2 = 1 and x3 = 5, what is the predicted value for y?

c. Supposed the n = 12 data points were used to construct the given regression equation above, and that the standard error for the coefficient x1 is 0.419. Construct a 90% confidence interval for the coefficient of x1.

d. Using the information from part (c) and 5% level of significance, test the claim that the coefficient of x1 is different from 0. What does your conclusion mean in relation to x1 predicting y?

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