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The last chapter covered the setup and configuration of the development environment. The development environment is an important necessity and will make the rest of your development more enjoyable. This chapter explores Web Forms. Web Forms bring the structure and fun back to Web development. This chapter starts by looking at the two programming models for ASP.NET. It then looks at how ASP.NET uses server controls and at the HTML (HyperText Markup Language) and Web server controls. It finishes by looking at view state and post back.

12-26 Consider the soil absorption data in Exercise 12-2 (a) Find a 95% confidence interval on the regression coefficient 1 (b) Find a 95% confidence interval on mean soil absorption index when x1 200 and x2 50 (c) Find a 95% prediction interval on the soil absorption index when x1 200 and x2 50 12-27 Consider the NFL data in Exercise 12-4 (a) Find a 95% confidence interval on 8 (b) What is the estimated standard error of Y |x0 when x2 2000 yards, x7 60%, and x8 1800 yards (c) Find a 95% confidence interval on the mean number of games won when x2 2000, x7 60, and x8 1800 12-28 Consider the gasoline mileage data in Exercise 12-5 (a) Find 99% confidence intervals on 1 and 6 (b) Find a 99% confidence interval on the mean of Y when x1 300 and x6 4.

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(c) Fit a new regression model to these data using x1, x2, x6, and x10 as the regressors Find 99% confidence intervals on the regression coefficients in this new model (d) Compare the lengths of the confidence intervals on 1 and 6 from part (c) with those found in part (a) Which intervals are longer Does this offer any insight about adding the variables x2 and x10 to the model 12-29 Consider the electric power consumption data in Exercise 12-6 (a) Find 95% confidence intervals on 1, 2, 3, and 4 (b) Find a 95% confidence interval on the mean of Y when x1 75, x2 24, x3 90, and x4 98 (c) Find a 95% prediction interval on the power consumption when x1 75, x2 24, x3 90, and x4 98 12-30 Consider the bearing wear data in Exercise 12-7 (a) Find 99% confidence intervals on 1 and 2.

Web Forms are an exciting part of the ASP.NET platform. Web Forms give the developer the ability to drag and drop ASP.NET server controls onto the form and easily program the events that are raised by the control. Web Forms have the following benefits: Rendering. Web Forms are automatically rendered in any browser. In addition, Web Forms can be tweaked to work on a specific browser to take advantage of its features.

(b) Recompute the confidence intervals in part (a) after the interaction term x1x2 is added to the model Compare the lengths of these confidence intervals with those computed in part (a) Do the lengths of these intervals provide any information about the contribution of the interaction term in the model 12-31 Consider the wire bond pull strength data in Exercise 12-8 (a) Find 95% confidence interval on the regression coefficients (b) Find a 95% confidence interval on mean pull strength when x2 20, x3 30, x4 90 and x5 20 (c) Find a 95% prediction interval on pull strength when x2 20, x3 30, x4 90, and x5 20 12-32 Consider the semiconductor data in Exercise 12-9 (a) Find 99% confidence intervals on the regression coefficients (b) Find a 99% prediction interval on HFE when x1 145, x2 220, and x3 50.

(c) Find a 99% confidence interval on mean HFE when x1 145, x2 220, and x3 50 12-33 Consider the heat treating data from Exercise 12-10 (a) Find 95% confidence intervals on the regression coefficients (b) Find a 95% confidence interval on mean PITCH when TEMP 1650, SOAKTIME 100, SOAKPCT 110, DIFFTIME 100, and DIFFPCT 080 12-34 Reconsider the heat treating data in Exercises 12-10 and 12-24, where we fit a model to PITCH using regressors x1 SOAKTIME SOAKPCT and x2 DIFFTIME DIFFPCT (a) Using the model with regressors x1 and x2, find a 95% confidence interval on mean PITCH when SOAKTIME 100, SOAKPCT 110, DIFFTIME 100, and DIFFPCT 080.

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