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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.

Short Answer

Expert verified

(a) For the variables volume and diameter, the regression inferences assumption is broken.

Step by step solution

01

Part (a) Step 1: Given information

Given in the question that, 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.
We need to decide that whether we can reasonably apply the regression t-lest. If so, then also do part (b).

02

Part (a) Step 2: Explanation

Given:

MINITAB is used to create the residual plot.

Minitab Procedure:

To begin, select Start > Regression > Regression.

Step 2: In the Response field, type VOLUME.

Step 3: Select Column DIAMETER in Predictors.

Step 4: In Graphs, under Residuals vs the variables, enter the columns DIAMETER.

Step 5: Click the OK button.

OUTPUT FROM MINITAB:

MINITAB is used to create a normal probability plot of residuals.

03

Part(a) Step 3: MINITAB procedure

Procedure with Minitab:

To begin, select Start > Regression > Regression.

Step 2: In the Response field, type VOLUME.

Step 3: Select Column DIAMETER in Predictors.

Step 4: Select Normal probability plot of residuals from the Graphs menu.

Step 5: Click the OK button.

OUTPUT FROM MINITAB:

The following is the assumption for regression inferences:

Line of population regression:

For each value of the predictor variable X, the conditional mean of the response variable (Y)isβ0+β1X.

Standard deviation equal:

The response variable's (Y)standard deviation is the same as the explanatory variable's (X)standard deviation.

The standard deviation is represented by the symbol σ.

Populations that are typical:

The response variable follows a normal distribution.

Independent Observations: The responses variable observations are unrelated to one another.

Examine whether the regression t-test is appropriate to use.

  • It is obvious from the residual plot that the residuals follow a curved concave rising pattern.
  • It is clear from the normal probability plot of residuals and the residual plot that there are outliers in the data. As a result, the residual plot has greater fluctuation than the standard probability map for residuals.

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Most popular questions from this chapter

14.22 Tax Efficiency. Tax efficiency is a measure ranging from 0 to 100 - of how much tax due to capital gains stock or mutual funds investors pay on their investments each year, the higher the tax efficiency, the lower the tax. The paper "At the Mercy of the Manager" (Financial Planning, Vol. 30(5), pp. 54-56 ) by C. Israelsen examined the relationship between investments in mutual fund portfolios and their associated tax efficiencies. The following table shows the percentage of investments in energy securities (x)and tax efficiency (y)for 10 mutual fund portfolios.

(a) Decide, at the 10%significance level, whether the data provide sufficient evidence to conclude that xis useful for predicting y:

(b) Find a 90%confidence interval for the slope of the population regression line.

14.96 Crown-Rump Length. Following are the data on age of fetuses and length of crown-rump from Exercise 14.26.

x
10
10
13
13
18
19
19
23
25
28
y
66
66
108
106
161
166
177
288
235
280

a. Determine a point estimate for the mean crown-rump length of all 19-week-old fetuses.
b. Find a 90% confidence interval for the mean crown-rump length of all 19-week-old fetuses.
c. Find the predicted crown-rump length of a 19-week-old fetus.

d. Determine a 90%prediction interval for the crown-rump length of a 19 -week-old fetus.

In Exercises 14.98-14.108, use the technology of your choice to do the following tasks.
a. Decide whether your can reasonably apply the conditional mean and predicted value t-interval procedures to the data. If so, then also do parts (b) - (h).
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%Te 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).

14.10 PCBs and Pelicans. The data from Exercise 14.40for shell thickness and concentration of PCBs of 60Anacapa pelican eggs are on the WeissStats site. Specified value of the predictor variable: 220ppm.

Following are the data on plant weight and quantity of volatile emissions.

α=0.05

presuming that the assumption for regression inference are met, decide at the specified significance level whether the data provide sufficient evidence to conclude that the predictor variable is useful for providing the response variable.

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