Question

An engineer wanted to determine how the weight of a car (kilograms), ?, affects fuel consumption (kilometers per litre), ?. The weights and fuel consumption for a random sample of 10 cars were recorded. Refer to the regression results from Excel.

Regression Statistics

Multiple R	0.84157604
R Square	0.708250231
Adjusted R Square	0.671781509
Standard Error	0.712010044
Observations	10

  

  

	Coefficients	Standard Error	t-Stat	P-Value	Lower 95%	Upper 95%
Intercept	15.883033	1.680071	9.453785	0.000013	12.008782	19.757285
X-Variable 1	-0.004384	0.000995	(?)	0.002266	-0.006679	-0.002090

a) Write the equation of the estimated least-squares regression line.

b) Test whether a linear relationship exists between weight of a car and fuel consumption at the ? = 0.01 level of significance. Use the critical value method.

c) Use the Excel output to write a 95% confidence interval for the slope of the true least-squares regression line. Interpret the result. Write a descriptive statement that could be easily understood by someone who is not in this statistics class.

d) A 95% prediction interval for ? = 1900 is 5.83 to 9.28. Interpret this result. Write a descriptive statement that could be easily understood by someone who is not in this statistics class.

Please be very clear with b the Hypothesis Test using critical value method. That is where I am having confusion.

Answer 1