partt I The following is a plot of the residuals versus fat for 26 menu items at

Question

partt I

The following is a plot of the residuals versus fat for 26 menu items at a fast food restaurant. Which of the following statements is supported by this plot?

a) A linear model is appropriate for explaining the relationship between the explanatory and response variables for this case.

b) There is evidence that the deviations described by the model are not Normal in distribution.

c) The abundance of outliers and influential observations in the plots means that the assumptions for regression are clearly violated.

d) None of the above

part II

The scatterplot below suggests a linear relationship between the age (in years) of an antique clock and its sale price (in euros) at auction. The data are age and sale price for 11 antique clocks sold at a recent auction.

We fit the least-squares regression line to the model Price = + (Age) where the deviations are assumed to be independent and Normally distributed, with mean 0 and standard deviation . A summary of the output is given: r2 = 0.848 s = 33.1559 Parameter Parameter estimate Std. err. of parameter est. 27.73 34.84 1.893 0.267 The intercept of the least-squares regression line is (approximately)

a) 27.73. b) 1.893. c) 34.84. d) 0.267.

part III

The scatterplot below suggests a linear relationship between the age (in years) of an antique clock and its sale price (in euros) at auction. The data are age and sale price for 11 antique clocks sold at a recent auction.

We fit the least-squares regression line to the model Price = + (Age) where the deviations are assumed to be independent and Normally distributed, with mean 0 and standard deviation . A summary of the output is given: r2 = 0.848 s = 33.1559 Parameter Parameter estimate Std. err. of parameter est. 27.73 34.84 1.893 0.267 An approximate 95% confidence interval for the slope in the simple linear regression model is

a) 1.289 to 2.497 euros per year. b) 1.289 to 2.497 euros. c) 1.289 to 2.497 years per euro. d) None of the above

Explanation / Answer

Solution:

Part 1

The correct answer is C

Explanation:

C. no of outliers are too many by visual inspection.

Part 2

From the given data,

We fit the least-squares regression line to the model Price = + (Age) is given by,

model Price = 27.73 + 1.893 (Age)

Therefore, The intercept = 27.73

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