Refer to Exercise 5. Here is computer output from the least-squares regression analysis of the beer and blood alcohol data.

a. What is the estimate for β₀? Interpret this value.

b. What is the estimate for β₁? Interpret this value.

c. What is the estimate for σ? Interpret this value.

d. Give the standard error of the slope SE_b1. Interpret this value.

Exercise 5.

How well does the number of beers a person drinks predict his or her blood alcohol content (BAC)? Sixteen volunteers aged 21 or older with an initial BAC of 0 took part in a study to find out. Each volunteer drank a randomly assigned number of cans of beer. Thirty minutes later, a police officer measured their BAC. A least-squares regression analysis was performed on the data using x = number of beers and y = BAC. Here is a residual plot and a histogram of the residuals. Check whether the conditions for performing inference about the regression model are met.

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Dependent variable is: BAC No Selector R squared = 80.0% R squared (adjusted) = 78.6% s = 0.0204 with 16 - 2= 14 degrees of freedom Variable prob 0.3320 Coefficient s.e. of Coeff t-ratio Constant -0.012701 0.0126 -1.00 Вeers 0.017964 0.0024 7.84 <0.0001