Highway crash data analysis. Researchers at Montana State University have written a tutorial on an empirical method for analyzing before and after highway crash data (Montana Department of...

Highway crash data analysis. Researchers at Montana State University have written a tutorial on an empirical method for analyzing before and after highway crash data (Montana Department of Transportation, Research Report, May 2004). The initial step in the methodology is to develop a Safety Performance Function (SPF)—a mathematical model that estimates crash occurrence for a given roadway segment. Using data collected for over 100 roadway segments, the researchers fit the model, E(y) = β₀
+ β₁x₁
+ β₂x₂, where y = number of crashes per 3 years, x₁
= roadway length (miles), and x₂
= AADT (average annual daily traffic) (number of vehicles). The results are shown in the following tables.

(a) Give the least squares prediction equation for the interstate highway model.

(b) Give practical interpretations of the β estimates, part a.

(c) Refer to part a. Find a 99% confidence interval for β₁
and interpret the result.

(d) Refer to part a. Find a 99% confidence interval for β₂
and interpret the result.

(e) Repeat parts a–d for the non-interstate highway model.