Find a confidence interval for and interpret the result

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Reference no: EM131403122

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.

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

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

(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.

Reference no: EM131403122

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