This example uses the Car Physical sample data table. A tire manufacturer wants to predict an engine’s horsepower from the engine’s displacement (in3). The company is most interested in estimating the slope of the relationship between the variables. The slope values help the company predict the corresponding change in horsepower when the displacement changes.
Select Help > Sample Data Library and open Car Physical
Select Analyze > Fit Y by X.
Select Horsepower and click Y, Response.
Select Displacement and click X, Factor.
Select Fit Line from the Bivariate Fit red triangle menu.
(Optional) Right-click in the Parameter Estimates report and select Columns > Lower 95%.
(Optional) Right-click in the Parameter Estimates report and select Columns > Upper 95%.
Right-click the Estimate column in the Parameter Estimates report and select Bootstrap (Figure 10.176).
Figure 10.176 The Bootstrap Option
The column that you right-click is relevant when the Split Selected Column option is selected. For more information, see Bootstrapping Window Options.
Type 1000 for the Number of Bootstrap Samples.
(Optional) To match the results in Figure 10.177, type 12345 for the Random Seed.
Figure 10.177 Bootstrap Report
The estimate of the slope (step 6) is 0.504. Based on the bootstrap results for 95% coverage, the company can estimate the slope to be between 0.40028 and 0.61892. When the displacement is changed by one unit, with 95% confidence, the horsepower changes by some amount between 0.40028 and 0.61892. The bootstrap confidence interval for the slope (0.400 to 0.619) is slightly wider than the confidence interval (0.425 to 0.583) obtained using the usual regression assumptions in step 7 and step 8.

Help created on 7/12/2018