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Gas Guzzlers. The data from Exercise 14.41 for gas mileage and engine displacement of 121 vehicles are on the WeissStats site. Specified value of the predictor variable: 3.0L.

a. Decide whether you can reasonably apply the conditional mean and predicted value t-interval procedures to the data. If so, then also do parts (b)-(f).

b. Determine and interpret a point estimate for the conditional mean of the response variable corresponding to the specified value of the predictor variable.

c. Find and interpret a 95%confidence interval for the conditional mean of the response variable corresponding to the specified value of the predictor variable.

d. Determine and interpret the predicted value of the response variable corresponding to the specified value of the predictor variable.

e. Find and interpret a 95%prediction interval for the value of the response variable corresponding to the specified value of the predictor variable.

f. Compare and discuss the differences between the confidence interval that you obtained in part (c) and the prediction interval that you obtained in part (e).

Short Answer

Expert verified

It is not applying the conditional mean and predicted value t-interval procedure to the given data in a reasonable manner. As a result, the remaining parts (b) -(f) are omitted.

Step by step solution

01

Given Information 

Given in the question that to consider the data's from exercise 14.41. Then we have to decide whether you can reasonably apply the conditional mean and predicted value t-interval procedures to the data. If so, then also do parts (b)-(f).

02

Explanation

Using the data from Exercise 14.41, determine whether it is possible to implement the conditional mean and preceded value 4 -interval procedure to data

.DISPMPG4161.8314153.5201.8263.2223221.8223232.8203192.5244.6182.8204.6192.8242243.1224183.8201.8273.8211.8273.8212.824

3203.2224.6203.2194.3152.5244.3154.6192.2264165.7202.5223.1223222.4242281.8312.4244.3171.8275.7133183.4192.4252.522323

3.2213.3152.5212.4233.3184192.2243.1242243.8203.3193.4193.9162235.2133.3183.3183.3192.7222.4235.2133.8212.5223.4182242.425

4.6192.5242282224.6132.3234161.9294.6161.9284182.5223212.2234.3152.2244.3151.6294.3173.4185.7133232.3252.225323323

2243221.6311.8303.2182222253192273.4192252243232293.3161.8243.2182.421

03

Explanation

As determined by the residual plot versus engine displacement. There is an upward concave curve pattern. The residual plot and the probability value of residuals show that there are outliers. As a result, the linear model is inapplicable.

As a result, for the variables Mpg and disp, assumption 1for regression inferences is violated. Furthermore, the interpretation for standard error obtained in part (a) is invalid.

As a result, able to apply the mean and predicted value t-interval procedure to the given data is not reasonable. As a result, the remaining parts (b) -(f) are omitted.

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Most popular questions from this chapter

Body Fat. In the paper "Total Body Composition by Dual-Photon ( G153id) Absorptiometry" (American Journal of Clinical Nutrition, Vol.40,pp.834-839), R. Mazess et al. studied methods for quantifying body composition. Eighteen randomly selected adults were measured for percentage of body fat, using dual-photon absorptiometry. Each adult's age and percentage of body fat are shown on the WeissStats site.

a. Decide whether you can reasonably apply the regression t-test. If so, then also do part (b).

b. Decide, at the 5%significance level, whether the data provide sufficient evidence to conclude that the predictor variable is useful for predicting the response variable.

To find and interpret a confidence interval , at the specified confidence level90% for the slope of the population regression line that relates the response variables to the predictor variable.

Following are the data on the percentage of investments in energy securities and tax efficiency95%,ฮฑ=0.05 . find and interpret a confidence interval, at the specified confidence level, for the slope of the population regression line that relates the response variable to the predictor variable.

The figure shows three residual plots and a normal probability plot of residuals. For each part, decide whether the graph suggests a violation of one or more of the assumptions for regression inferences. Explain your answers.

The data from Exercise 14.43 for volume, in cubic feet, and diameter at breast height, in inches, for 70 shortleaf pines are on the WeissStats site.

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