Use the data in the table, which shows the personal income and outlays (both in trillions of dollars) for Americans for 11 recent years. (Source: U.S. Commerce Department, Bureau of Economic Analysis)

Personal income, x

5.6 4.6

5.8 4.9

6.2 5.2

6.5 5.5

6.9 5.8

7.4 6.1

7.8 6.5

8.4 7.0

8.7 7.3

8.9 7.7

9.2 8.0

1. Construct a scatter plot for the data. Do the data appear to have a positive linear correlation, a negative linear correlation, or no linear correlation? Explain.
2. Calculate the correlation coefficient r. What can you conclude?
3. Test the level of significance of the correlation coefficient r. Use  =0.05.
4. Find the equation of the regression line for the data. Include the regression line in the scatter plot.
5. Use the regression line to predict the personal outlays when the personal income is 5.3 trillion dollars.
6. Find the coefficient of determination and interpret the results.
7. Find the standard error of estimate s e and interpret the results.
8. Construct a 95% prediction interval for personal outlays when personal income is 6.4 trillion dollars. Interpret the results.
9. The equation used to predict sunflower yield (in pounds) is :

ŷ = 1257 - 1.34 x 1 + 1.41 x 2

w here x 1 is the number of acres planted (in thousands) and x 2 is the number of acres harvested (in thousands). Use the regression equation to predict the y-values for the given values of the independent variables listed below. Then determine which variable has a greater influence on the value of y . (Source: U.S. National Agricultural Statistics Service)

1. x1 = 2103, x2 = 2037
2. x1 = 3387, x2 = 3009
3. x1 = 2185, x2= 1980
4. x1 = 3485, x2 = 3404

4. A legal researcher is studying the age distribution of juries by comparing them with the o verall age distribution of available jurors. The researcher claims that the jury distribution is d ifferent from the overall distribution; that is, there is a noticeable age bias in jury selection in this area. The table shows the number of jurors at a county court in one year and the percent of persons residing in that county, by age. Use the population distribution to find the expected juror frequencies. Test the researcher’s claim at  = 0.01. Use a n x-squared g oodness-of-fit test to test the claim about the population distribution. Interpret the d ecision in the context of the original claim.

Jury 45 128 244 224 359

Population

16. A steel pipe fittings company claims that the yield strength of its non-tempered couplings is more variable than that of its tempered couplings. A random sample of nine tempered couplings has a standard deviation of 13.1 megapascals , and a similar sample of nine non-tempered couplings has a standard deviation of 25.4 megapascals . From past data, it is known that the company’s production process results in normally distributed yield strengths. Test the company’s claim at  =0.05. Test the claim about two population variances at the indicated level of significance  . Interpret the results in the context of the claim.

Price: $18.46

Solution: The downloadable solution consists of 9 pages, 946 words and 3 charts.
Deliverable: Word Document