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.
Theodore Brookhart and Egmont C. Arens, "Streamliner" Meat Slicer, Model 410.
Types of ecosystem service vs. total global value per year
Hepatic Acinus Model of Liver Function
Heart - All I Wanna Do Is Make Love To You (Official Music Video)
The attenuation model regulating the tryptophan operon
The Gene Expression Machine Model for Coupling