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Home Size and Value. The data from Exercise 14.38 for home size (in square feet) and assessed value (in thousands of dollars) for the same homes as in Exercise 14.73 are on the WeissStats site.

Short Answer

Expert verified

(a)For the variables value and home size, assumption 3 for regression inferences is broken.

Step by step solution

01

Part (a) Step 1: Given information

Given in the question that, Home Size and Value. The data from Exercise 14.38 for home size (in square feet) and assessed value (in thousands of dollars) for the same homes as in Exercise 14.73 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.

Procedure with Minitab:

First, select Start > Regression > Regression.

Step 2: In the Response box, type VALUE in the Column field.

Step 3: Select Column HOME SIZE in Predictors.

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

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: Construct the residual plot

Procedure with Minitab:

First, select Start > Regression > Regression.

Step 2: In the Response box, type VALUE in the Column field.

Step 3: Select Column HOME SIZE 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 Xof the predictor variable, the conditional mean of the response variable (Y)is β0+β1X.

The standard deviation for the response variable $(Y)$ and the standard deviation for the explanatory variable $(X)$ are the same. The standard deviation is represented by the symbol $\sigma$.

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.

  • It's evident from the residual plot that the residuals are in the horizontal band.
  • It is obvious from the normal probability plot of residuals that the residuals do not follow the linear pattern.

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Most popular questions from this chapter

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.

14.97 Study Time and Score. Following are the data on total hours studied over 2 weeks and test score at the end of the 2 weeks from Exercise 14.27.

x
10
15
12
20
8
16
14
22
y
91
81
84
74
85
80
84
80


a. Determine a point estimate for the mean test score of all beginning calculus students who study for 15hours.
b. Find a 99% confidence interval for the mean test score of all beginning calculus students who study for 15 hours.
c. Find the predicted test score of a beginning calculus student who studies for 15 hours.
d. Determine a 99% prediction interval for the test score of a beginning calculus student who studies for 15hours.

14.25 Plant Emissions. Plants emit gases that trigger the ripening of fruit, attract pollinators, and cue other physiological responses. N. Agelopolous et al. examined factors that affect the emission of volatile compounds by the potato plant Solanum tuberosum and published their findings in the paper "Factors Affecting Volatile Emissions of Intact Potato Plants, Solanum tuberosum: Variability of Quantities and Stability of Ratios" (Journal of Chemical Ecology, Vol. 26(2), pp. 497-511). The volatile compounds analyzed were hydrocarbons used by other plants and animals. Following are data on plant weight (x), in grams, and quantity of volatile compounds emitted (y), in hundreds of nanograms, for 11 potato plants.

Based on a sample of data points, what is the best estimate of the population regression line?

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.

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