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Acreage and Value. The data from Exercise 14.37 for lot size (in acres) and assessed value (in thousands of dollars) of a sample of homes in a particular area are on the WeissStats site. Do the data provide sufficient evidence to conclude that, for homes in this particular area, lot size and assessed value are positively linearly correlated?

Short Answer

Expert verified

Thus, the data do not provide sufficient evidence to conclude that, for homes in this particular area, lot size and assessed value are positively linearly correlated at 5%significance level.

Step by step solution

01

Step 1:Given information

The data from Exercise 14.37 for lot size (in acres) and assessed value (in thousands of dollars) of a sample of homes in a particular area are on the WeissStats site

02

Step 2:Explaination

Check whether or not it is reasonably apply the correlation t-test procedure by using the data from Exercise 14.37.

- From the residual plot, it is clear that the residuals are falls in the horizontal band.

- From the normal probability plot of residuals, it is clear that the residuals are roughly linear pattern.

Hence, the assumptions 1-3 for the regression inferences are not violated for the variables value and lot size. But from Exercise 14.73, it is clear that the observations are not linear pattern.

Check whether the data provide sufficient evidence to conclude that, for homes in this particular area, lot size and assessed value are positively linearly correlated.

The test hypotheses are as follows:

Null hypothesis:

H0:ρ=0

That is, lot size and assessed value for homes are not positively linearly correlated.

Alternative hypothesis:

Ha:ρ>0

That is, lot size and assessed value for homes are positively linearly correlated.

Obtain the correlation and p-value between lot size and value by using MINITAB.

MINITAB procedure:

Step 1: Select Stat >Basic Statistics > Correlation.

Step 2: In Variables, select lot size and value from the box on the left.

Step 3: Click OK.

MINITAB output:

Conclusion:

Use the significance level, α=0.05.

Here, p-value is greater than the level of significance.

That is, p-value (=0.1345)>α(=0.05).

Therefore, by the rejection rule, it can be concluded that there is no evidence to reject the null hypothesis H0at α=0.05.

Thus, the data do not provide sufficient evidence to conclude that, for homes in this particular area, lot size and assessed value are positively linearly correlated at 5%significance level.

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Most popular questions from this chapter

In this Exercise 14.53, we repeat the information from Exercise 14.17.

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.

role="math" localid="1652352243033" x22344y34021 y^=5-x

In Exercises 14.48-14.57, we repeat the information from Exercises 14.12-14.21.

a. Decide, at the 10%significance level, whether the data provide sufficient evidence lo conclude that a is useful for predicting y:

b. Find a 90%confidences interval for the slope of the population regression line.

y=1.75+0.25x

In Exercises 14.12-14.21, we repeat the data and provide the sample regression equations for Exercises 4.48-4.57.

a. Determine the standard error of the estimate.

b. Construct a residual plot.

c. Construct a normal probability plot of the residuals.

In Exercises 14.98-14.108, use the technology of your choice to do the following tasks.
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).

14.98 Birdies and Score. The data from Exercise 14.34 for number of birdies during a tournament and final score of 63 women golfers are on the WeissStats site. Specified value of the predictor variable:12birdies.

Following are the data on age of fetuses and length of crown-rump.useα=0.10presuming 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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