Question

Use the data from Chapter 11, Problem 12, answer the following questions: (1) Estimate the slope and intercept of the least squares regression model. (2) Predict the power consumption for an ambient temperature of 65 degreess Fahrenheit. (3) Evaluate s2. (4) Test the hypothesis H0 : β1 = 0 vs. H1 : β1 6= 0 at α = 0.05 level of significance and interpret the resulting decision. (5) Find the coefficient of determination and interpret the meaning. (6) Construct a 95% confidence interval for β1. (7) Construct a 95% confidence interval for the mean power consumption when x = 65◦F. (8) Construct a 95% prediction interval for a single predicted value of power consumption when x = 65◦F.

Answer 1

Answer:

Check the explanation

Step-by-step explanation:

Check the first attached image below for question 1.

Equation-> y=218.255+1.384x

2)y(65)=218.255+1.384*65=308.211

3)s2=4.02^2=16.2

4)pvalue of x=2.79E-6. Hence β1 is significant.

5)R^2=0.9793. This means about 98% of the variation in x is explained by y.

Check the second attached image below for question 6.

7)Confidence Interval->[303.6248,312.7975]

8)Prediction Interval->[297.3579,319.0644]