Applied Statistics and Probability for Engineers 6th Edition solutions

Applied Statistics and Probability for Engineers 6
Consider the regression model fit to the nisin extraction data in Exercise 12-18. (a) Calculate 95% confidence intervals on each regression coefficient. (b) Calculate a 95% confidence interval on mean nisin extraction when \(x_1=15.5\) and \(x_2=16\). (c) Calculate a prediction interval o

Applied Statistics and Probability for Engineers 6
Using the regression model from Exercise 12-1, (a) Find a \(95 \%\) confidence interval for the coefficient of height. (b) Find a \(95 \%\) confidence interval for the mean percent of body fat for a man with a height of 72in and waist of 34in. (c) Find a \(95 \%\) prediction interval for the percent

Applied Statistics and Probability for Engineers 6
Using the regression from Exercise 12-2, (a) Find a \(95 \%\) confidence interval for the coefficient of hourly 1 test. (b) Find a \(95 \%\) confidence interval for the mean final grade for students who score 80 on the first test and 85 on the second. (c) Find a \(95 \%\) prediction interval for a st

Applied Statistics and Probability for Engineers 6
Referring to the regression model from Exercise 12-3, (a) Find a \(95 \%\) confidence interval for the coefficient of spending on higher education. (b) Is zero in the confidence interval you found in part (a)? What does that fact imply about the coefficient of higher education? (c) Find a \(95 \%\) p

Applied Statistics and Probability for Engineers 6
Use the second-order polynomial regression model from Exercise 12-4, (a) Find a \(95 \%\) confidence interval on both the first-order and the second-order term in this model. (b) Is zero in the confidence interval you found for the second-order term in part (a)? What does that fact tell you about the

Applied Statistics and Probability for Engineers 6
Consider the regression model fit to the shear strength of soil in Exercise 12-5. (a) Calculate \(95 \%\) confidence intervals on each regression coefficient. (b) Calculate a \(95 \%\) confidence interval on mean strength when \(x_{1}=18 \mathrm{ft} \text { and } x_{2}=43 \%\) (c) Calculate \(95 \%\

Applied Statistics and Probability for Engineers 6
Consider the soil absorption data in Exercise 12-6. (a) Find \(95 \%\) confidence intervals on the regression coefficients. (b) Find a \(95 \%\) confidence interval on mean soil absorption index when \(x_{1}=200 \text { and } x_{2}=50\). (c) Find a \(95 \%\) prediction interval on the soil absorptio

Applied Statistics and Probability for Engineers 6
Consider the semiconductor data in Exercise 12-13. (a) Find \(99 \%\) confidence intervals on the regression coefficients. (b) Find a \(99 \%\) prediction interval on HFE when \(x_{1}=14.5, x_{2}=220, \text { and } x_{3}=5.0\) (c) Find a \(99 \%\) confidence interval on mean HFE when \(x_{1}=14.5,

Applied Statistics and Probability for Engineers 6
Consider the electric power consumption data in Exercise 12-10. (a) Find \(95 \%\) confidence intervals on \(\beta_{1}, \beta_{2}, \beta_{3}, \text { and } \beta_{4}\). (b) Find a \(95 \%\) confidence interval on the mean of Y when \(\mathrm{x}_{1}=75, \mathrm{x}_{2}=24, \mathrm{x}_{3}=90, \text { a

Applied Statistics and Probability for Engineers 6
Consider the bearing wear data in Exercise 12-23. (a) Find 99% confidence intervals on \(\beta_{1}\) and \(\beta_{2}\). (b) Recompute the confidence intervals in part (a) after the interaction term \(\mathrm{x}_{1} \mathrm{X}_{2}\) is added to the model. Compare the lengths of these confidence interv

Applied Statistics and Probability for Engineers 6
Consider the wire bond pull strength data in Exercise 12-12. (a) Find 95% confidence interval on the regression coefficients. (b) Find a 95% confidence interval on mean pull strength when \(x_{2}=20, x_{3}=30, x_{4}=90\), and \(x_{5}=2.0\). (c) Find a 95% prediction interval on pull strength w

Applied Statistics and Probability for Engineers 6
Consider the regression model fit to the X-ray inspection data in Exercise 12-15. Use rads as the response. (a) Calculate \(95 \%\) confidence intervals on each regression coefficient. (b) Calculate a \(99 \%\) confidence interval on mean rads at 15 milliamps and 1 second on exposure time. (c) Calcul

Applied Statistics and Probability for Engineers 6
Consider the regression model fit to the arsenic data in Exercise 12-16. Use arsenic in nails as the response and age, drink use, and cook use as the regressors. (a) Calculate \(99 \%\) confidence intervals on each regression coefficient. (b) Calculate a \(99 \%\) confidence interval on mean arsenic

Applied Statistics and Probability for Engineers 6
Consider the regression model fit to the coal and limestone mixture data in Exercise 12-17. Use density as the response. (a) Calculate \(90 \%\) confidence intervals on each regression coefficient. (b) Calculate a \(90 \%\) confidence interval on mean density when the dielectric constant = 2.3 and t

Applied Statistics and Probability for Engineers 6
Problem 62E Consider the regression model fit to the nisin extraction data in Exercise 12-18. (a) Calculate 95% confidence intervals on each regression coefficient. (b) Calculate a 95% confidence interval on mean nisin extraction when x1 = 15.5 and x2 = 16.

Applied Statistics and Probability for Engineers 6
Consider the regression model fit to the gray range modulation data in Exercise 12-19. Use the useful range as the response. (a) Calculate \(99 \%\) confidence intervals on each regression coefficient. (b) Calculate a \(99 \%\) confidence interval on mean useful range when brightness = 70 and contras

Applied Statistics and Probability for Engineers 6
Consider the stack loss data in Exercise 12-20. (a) Calculate \(95 \%\) confidence intervals on each regression coefficient. (b) Calculate a \(95 \%\) confidence interval on mean stack loss when \(x_{1}=80, x_{2}=25 \text { and } x_{3}=90 \text {. }\) (c) Calculate a prediction interval on stack los

Applied Statistics and Probability for Engineers 6
Consider the NFL data in Exercise 12-21. (a) Find 95% confidence intervals on the regression coefficients. (b) What is the estimated standard error of \(\hat{\mu}_{Y \mid x_{0}}\) when the percentage of completions is 60%, the percentage of TDs is 4%, and the percentage of interceptions is

Applied Statistics and Probability for Engineers 6
Consider the heat-treating data from Exercise . (a) Find \(95 \%\) confidence intervals on the regression coefficients. (b) Find a \(95 \%\) confidence interval on mean PITCH when TEMP \(=1650\), SOAKTIME \(=1.00\), SOAKPCT \(=1.10\) DIFFTIME \(=1.00\), and DIFFPCT \(=0.80\). (c) Fit a model to PITC

Applied Statistics and Probability for Engineers 6
Consider the gasoline mileage data in Exercise . (a) Find \(99 \%\) confidence intervals on the regression coefficients. (b) Find a \(99 \%\) confidence interval on the mean of \(Y\) for the regressor values in the first row of data. (c) Fit a new regression model to these data using cid, etw, and ax

Applied Statistics and Probability for Engineers 6
Consider the NHL data in Exercise 12-22. (a) Find a \(95 \%\) confidence interval on the regression coefficient for the variable GF. (b) Fit a simple linear regression model relating the response variable to the regressor GF. (c) Find a \(95 \%\) confidence interval on the slope for the simple linear