The maintenance costs incurred over the past year for a particular make, model, and year of automobile are given below, along with each car's end-of-year mileage. Use technology to compute a p-value and use it to determine whether the regression equation is useful for making predictions about maintenance costs for this automobile model. Test at the 1% significance level with the hypotheses H
0: β
1 = 0 and
Make sure to eliminate any outliers and/or influential points from the data.
◦ p = 0.00014. Since p < α, reject the null hypothesis. The regression equation is useful for making maintenance cost predictions.
◦ p = 0.00014. Since p < α, do not reject the null hypothesis. The regression equation is not useful for making maintenance cost predictions.
◦ p = 0.02317. Since p > α, do not reject the null hypothesis. The regression equation is not useful for making maintenance cost predictions.
◦ p = 0.02317. Since p > α, reject the null hypothesis. The regression equation is useful for making maintenance cost predictions.
A space-filling model of the DNA double helix
A model for synthetic lethality
Lab: Paramecium Model
Tuition Costs
An additive model for the inheritance of height in the Potsdam Guards. In this example, the guards a
Model for ecosystems on land