Question

The Toyota Camry is one of the best-selling cars in North America. The cost of a previously owned Camry depends on many factors, including the model year, mileage, and condition. To investigate the relationship between the car’s mileage and the sales price for Camrys, the following data show the mileage and sale price for 19 sales (PriceHub web site, February 24, 2012).

	Miles (1,000s)		Price ($1,000s)
	22		16.2
	29		16.0
	36		13.8
	47		11.5
	63		12.5
	77		12.9
	73		11.2
	87		13.0
	92		11.8
	101		10.8
	110		8.3
	28		12.5
	59		11.1
	68		15.0
	68		12.2
	91		13.0
	42		15.6
	65		12.7
	110		8.3

(a)	Choose a scatter chart below with ‘Miles (1000s)’ as the independent variable.
	(i) (ii) (iii) (iv)
	- Select your answer -Chart (i)Chart (ii)Chart (iii)Chart (iv)Item 1
	What does the scatter chart indicate about the relationship between price and miles?
	The scatter chart indicates there may be a - Select your answer -positivenegativeItem 2  linear relationship between miles and price. Since a Camry with higher miles will generally sell for a lower price, a negative relationship is expected between these two variables. This scatter chart is consistent with what is expected.
(b)	Develop an estimated regression equation showing how price is related to miles. What is the estimated regression model?
	Let x represent the miles.
	If required, round your answers to four decimal places. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300)
	=   +  x
(c)	Test whether each of the regression parameters β0 and β1 is equal to zero at a 0.01 level of significance. What are the correct interpretations of the estimated regression parameters? Are these interpretations reasonable?
	The input in the box below will not be graded, but may be reviewed and considered by your instructor.
(d)	How much of the variation in the sample values of price does the model estimated in part (b) explain?
	If required, round your answer to two decimal places.
	%
(e)	For the model estimated in part (b), calculate the predicted price and residual for each automobile in the data. Identify the two automobiles that were the biggest bargains.
	If required, round your answer to the nearest whole number.
	The best bargain is the Camry #  in the data set, which has   miles, and sells for $  less than its predicted price. The second best bargain is the Camry #  in the data set, which has   miles, and sells for $  less than its predicted price.
(f)	Suppose that you are considering purchasing a previously owned Camry that has been driven 70,000 miles. Use the estimated regression equation developed in part (b) to predict the price for this car.
	If required, round your answer to one decimal place. Do not round intermediate calculations.
	Predicted price: $
	Is this the price you would offer the seller?
	- Select your answer -YesNoItem 14
	Explain.
	The input in the box below will not be graded, but may be reviewed and considered by your instructor.

Answer 1

BY USING EXCEL WE HAVE

the estimated regression model

y(hat)=16.4698-0.0588*X

C] FROM ABOVE TABLE WE CAN SEE THAT Pvalue for Intercept coefficient  β_{0 is significant since Pvalue is 0.000000000000298 which is smaller than the level of significance 0.01 . So it is significant}

Pvalue for  β1 is _{is significant since Pvalue is 0.00034 which is smaller than the level of significance 0.01 . So it is significant .}

D] R squared is 0.5387 or 53.87%

NOTE : AS PER THE GUIDELINES I HAVE DONE THE FIRST FOUR PLEASE RE POST THE REST ALONG WITH THE DATA. THANK YOU