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U.S. Presidents. The data from Exercise 14.35 for the ages at inauguration and of death of the presidents of the United States are on the WeissStats site. Do the data provide sufficient evidence to conclude that, for U.S. presidents, age at inauguration and age at death are positively linearly correlated?

Short Answer

Expert verified

For U.S. presidents, age at inauguration and age at death are positively linearly correlated at 5% significance level.

Step by step solution

01

Step 1:Given information

The data from Exercise 14.35 for the ages at inauguration and of death of the presidents of the United States 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 14.35.

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

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

Hence, the assumptions for the regression inferences are not violated for the variables inauguration and death.

Check whether the data provide sufficient evidence to conclude that, for U.S. presidents, age at inauguration and age at death are positively linearly correlated.

The test hypotheses are as follows:

Null hypothesis:

H0:ÒÏ=0

That is, the inauguration ages and the death ages of U.S. presidents are not positively linearly correlated.

Alternative hypothesis:

Ha:ÒÏ>0

That is, the inauguration ages and the death ages of U.S. presidents are positively linearly correlated.

Obtain the correlation and P-value between inauguration and death by using MINITAB.

MINITAB procedure:

Step 1: Select Stat >Basic Statistics > Correlation.

Step 2: In Variables, select inauguration and death from the box on the left.

Step 3: Click OK.

MINITAB output:

Correlation: INAUGURATION, DEATH

Pearson correlation of INAUGURATION and DEATH =0.606

P-Value=0.000

From the above MINITAB output, the value of correlation between inauguration and death is

0.606and the P-value for right-tail test is 0.000=0.0002.

Conclusion:

Use the significance level, α=0.05.

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

That is, p-value (=0.000)<α(=0.05).

Therefore, by the rejection rule, it can be concluded that there is evidence to reject the null hypothesis H0at α=0.05

Thus, the data provide sufficient evidence to conclude that, for U.S. presidents, age at inauguration and age at death are positively linearly correlated at 5%significance level.

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Most popular questions from this chapter

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

PCBs and Pelicans. Use the data points given on the WeissStats site for shell thickness and concentration of PCBs for 60 Anacapa pelican eggs referred to in Exercise 14.40.

U.S. Presidents. The Information Please Almanac provides data on the ages at the inauguration and death of the presidents of the United States. We give those data on the WeissStats site for those residents who are not still living at the time of this writing.

14.93 Corvette Prices. Following are the age and price data for Corvettes from Exercise 14.23.

x
6
6
6
2
2
5
4
5
1
4
y
290
280
295
425
384
315
355
328
425
325

a. Obtain a point estimate for the mean price of all 4-year-old Corvettes.

b. Determine a 90% confidence interval for the mean price of all 4-year-old Corvettes.

c. Find the predicted price of a 4-year-old Corvette.
d. Determine a 90% prediction interval for the price of a 4 -year-old Corvette.
e. Draw graphs similar to those in Fig. 14.11 on page 576 , showing
f. Why is the prediction interval wider than the confidence interval?

For two variables satisfying Assumptions 1-3 for regression inferences, the population regression equation is y=20-3.5x. For samples of size 10 and given values of the predictor variable, the distribution of slopes of all possible sample regression lines is a --------distribution with mean------- .

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