Construct the indicated prediction interval and interpret the results.

The total assets in equity funds is $900 billion. Construct a prediction interval for the total assets in bond and income funds. Use the results of Exercise 16 and c = 0.90.

Use the standard error to construct an approximate prediction interval for $Y$. Based on the width of this prediction interval, would you say the predictions are good enough to have practical value?

Use the standard error to construct an approximate prediction interval for $Y$. Based on the width of this prediction interval, would you say the predictions are good enough to have practical value?

Writing Given a set of data and a corresponding regression line, describe all values of x that provide meaningful predictions for y.

Use the data to find the

(a) coefficient of determination $r^2$ and interpret the result with regard to the regression line, and

(b) the standard error of estimate $s_e$ and interpret the result.

The table shows the prices of 16 gas grills (in U.S. dollars) and their usable cooking area (in square inches). The regression equation is $\hat{y}$ = 1.305x - 209.506.

The table shows the area of eight living spaces (in square feet) and the cooling capacity (in Btu per hour) of the air conditioners used in those spaces. The regression equation is

$\hat{y}$=9.468 x+3002.991

Find the

a) coefficient of determination $r^2$ and interpret the result,

b) standard error of estimate $s_{\mathrm{c}}$ and interpret the result.

An instructor wants to show students that there is a linear correlation between the number of hours they spend online during a weekend and their scores on a test taken the following Monday. The number of hours spent online and the test scores for 12 randomly selected students are shown in the table. At $\alpha=0.05$, is there enough evidence for the instructor to conclude that there is a significant linear correlation between the data?

Use the mentioned table as shown in the mentioned example or perform a hypothesis test using the mentioned table as shown in the mentioned example to make a conclusion about the indicated correlation coefficient. If convenient, use technology to solve the problem.

In this exercise, use the said table as shown in the earlier example or perform a hypothesis test using the other said table as shown in the earlier example to make a conclusion about the indicated correlation coefficient . Also, if convenient, use technology to solve the problem .

You randomly select 14 men and measure the height (in inches) and shoe size of each. The data are listed below. At $\alpha=0.05$, can you conclude that there is a significant linear correlation between the men's shoe sizes and heights? (Use the value of r found in the earlier exercise.)

$$\begin{aligned} &\begin{array}{|l|c|c|c|c|c|c|c|} \hline \text { Shoe size, } \boldsymbol{x} & 8.5 & 9.0 & 9.0 & 9.5 & 10.0 & 10.0 & 10.5 \\ \hline \text { Height, } \boldsymbol{y} & 66.0 & 68.5 & 67.5 & 70.0 & 70.0 & 72.0 & 71.5 \\ \hline \end{array}\\ &\begin{array}{|l|l|l|l|l|l|l|l|} \hline \text { Shoe size, } \boldsymbol{x} & 10.5 & 11.0 & 11.0 & 11.0 & 12.0 & 12.0 & 12.5 \\ \hline \text { Height, } \boldsymbol{y} & 69.5 & 71.5 & 72.0 & 73.0 & 73.5 & 74.0 & 74.0 \\ \hline \end{array} \end{aligned}$$

Writing Explain how to predict y-values using the equation of a regression line.

In exercise,

(a) display the data in a scatter plot,

(b) calculate the correlation coefficient r, and

(c) make a conclusion about the type of correlation.

The number of crimes reported (in millions) and the number of arrests reported (in millions) by the FBI for 11 years.

Construct the indicated prediction interval and interpret the results.

A total of $775.8 million is raised in one year for congressional campaigns . Construct a prediction interval for the money spent by the campaigns. Use the results of Exercise 15 and c = 0.95.

The number of hours 13 students spent studying for a test and their scores on that test is shown in the table. Is there enough evidence to conclude that there is a significant linear correlation between the data? Use $\alpha=0.01$.

Use the mentioned table as shown in the mentioned example or perform a hypothesis test using the mentioned table as shown in the mentioned example to make a conclusion about the indicated correlation coefficient. If convenient, use technology to solve the problem.

Construct the indicated prediction interval and interpret the results.

When the voting age population is 190 million, construct a 99% prediction interval for the voter turnout in federal elections. Use the results of Exercise 14.

In exercise,

(a) display the data in a scatter plot,

(b) calculate the correlation coefficient r, and

(c) make a conclusion about the type of correlation.

The earnings per share and dividends per share for 10 electric utility companies in a recent year.