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Chapter 14: Q. 14.125 (page 585)

In Exercises \(14.118-14.127\). we repeat the data from Exercises \(14.12-14.21\) and specify an alternative hypothesis for a correlation \(t-\)test. For each exercise, decide at the \(10%\) significance level. whether the data provide sufficient evidence to reject the null hypothesis in favor of the alternative hypothesis.

\(H_{a}:\rho>0\)

Short Answer

Expert verified

Since, the \(P-\)value is greater than the level of significance.

Thus, the null hypothesis is not rejected.

Step by step solution

01

Step 1. Given information

The level of significance is \(0.1\) and the data is,

02

Step 2. Calculation

The hypothesis are,

\(H_{0}:\rho=0\)

\(H_{a}:\rho>0\)

The MINITAB output is shown below.

Since, the \(P-\)value is greater than the level of significance.

Thus, the null hypothesis is not rejected.

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Most popular questions from this chapter

Use the data on the Weiss Stats site for estriol levels of pregnant women and birth weights of their children referred to in Exercise 14.42.

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
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y
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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.

High and Low Temperature. The data from Exercise 14.39for average high and low temperatures in January for a random sample of 50cities are 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.

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.

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

a. Deride, at the lore significance level, whether the data provide sufficient evidence to conclude that xis useful for predicting y.

b. Find a localid="1653240248143" 90%confidence interval for the slope of the population regression line.

y=1+2x
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