Back"In Exercises 19-24, construct the indicated prediction interval and interpret the results.
19. Construct a 90% prediction interval for the amount of milk produced in Exercise 9 when there are an average of 9275 thousand milk cows."
"In Exercises 19-24, construct the indicated prediction interval and interpret the results.
24. Construct a 99% prediction interval for the price of a gas grill in Exercise 18 with a usable cooking area of 900 square inches."
"Confidence Intervals for y-Intercept and Slope
You can construct confidence intervals for the y-intercept B and slope M of the regression line y = Mx + B for the population by using the inequalities below.
y-intercept B :
b - E < B < b + E
where
E = t_c s_e \sqrt{\frac{1}{n} + \frac{\overline{x}^2}{\sum x^2 - \frac{(\Sigma x)^2}{n}}}
slope M :
m - E < M < m + E
where
E = \frac{t_c s_e}{\sqrt{\sum x^2 - \frac{(\Sigma x)^2}{n}}}
The values of m and b are obtained from the sample data, and the critical value t_c is found using Table 5 in Appendix B with n - 2 degrees of freedom.
In Exercises 37 and 38, construct the indicated confidence intervals for B and M using the gross domestic products and carbon dioxide emissions data found in Example 2.
38. 99% confidence interval"
"[APPLET] For Exercises 1–8, use the data in the table, which shows the average annual salaries (both in thousands of dollars) for secondary and elementary school teachers, excluding special and vocational education teachers, in the United States for 11 years. (Source: U.S. Bureau of Labor Statistics)
8. Construct a 95% prediction interval for the average annual salary of elementary school teachers when the average annual salary of secondary school teachers is \$63,500. Interpret the results."
[NOW WORK] Using the sample data from Problem 5 in Section 12.3,
d. Construct a 95% prediction interval for the value of y if x=7.
Using the sample data from Problem 6 in Section 12.3,
d. Construct a 95% prediction interval for the value of y if x=8.
Using the sample data from Problem 7 in Section 12.3
b. Construct a 95% confidence interval for the mean value of y if x=1.4.
Credit Scores Use the results of Problem 12 from Section 12.3 to answer the following questions:
b. Construct a 90% confidence interval for the mean interest rate of all individuals whose credit score is 730.
Credit Scores Use the results of Problem 12 from Section 12.3 to answer the following questions:
d. Construct a 90% prediction interval for the interest rate of Kaleigh, whose credit score is 730.
Hurricanes Use the results of Problem 14 in Section 12.3 to answer the following questions:
b. Construct a 95% confidence interval for the mean wind speed found in part (a).
Hurricanes Use the results of Problem 14 in Section 12.3 to answer the following questions:
d. Construct a 95% prediction interval for the wind speed found in part (c).
Tar and Nicotine Use the results of Problem 16 in Section 12.3 to answer the following questions:
b. Construct a 95% confidence interval for the tar content found in part (a).
Standard Error of Estimate A random sample of 118 different female statistics students is obtained and their weights are measured in kilograms and in pounds. Using the 118 paired weights (weight in kg, weight in lb), what is the value of se? For a female statistics student who weighs 100 lb, the predicted weight in kilograms is 45.4 kg. What is the 95% prediction interval?
Invest in Education Use the results of Problem 17 in Section 12.3 to answer the following questions:
b. Construct a 95% confidence interval for the mean annual ROI found in part (a).
Interpreting a Computer Display
In Exercises 9–12, refer to the display obtained by using the paired data consisting of weights (pounds) and highway fuel consumption amounts (mi/gal) of the large cars included in Data Set 35 “Car Data” in Appendix B. Along with the paired weights and fuel consumption amounts, StatCrunch was also given the value of 4000 pounds to be used for predicting highway fuel consumption.
Finding a Prediction Interval For a car weighing 4000 pounds (x = 4000) identify the 95% prediction interval estimate of the highway fuel consumption. Write a statement interpreting that interval.