Need help with some Stats please .. Thanks

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You may need to use the appropriate appendix table or technology to answer this question. Many small restaurants in Portland, Oregon, and other cities across the United States do not take reservations. Owners say that with smaller capacity, noshows are costly, and they would rather have their staff focused on customer service rather than maintaining a reservation system.+ However, it is important to be able to give reasonable estimates of waiting time when customers arrive and put their name on the waiting list. The file RestaurantLine contains 10 observations of number of people in line ahead of a customer (independent variable x) and actual waiting time (in minutes) (dependent variable y). The estimated regression equation is: f = 4.35 + 8.81)! and MSE = 94.42. (a) Develop a point estimate (in min) for a customer who arrives with four people on the waitlist. {Round your answer to two decimal places.) r = :mm (b) Develop a 95% condence interval for the mean waiting time (in min) for a customer who arrives with four customers already in line. {Round your answers to two decimal places.) l | min to | min (c) Develop a 95% prediction interval for Roger and Sherry Davy's waiting time (in min) if there are four customers in line when they arrive. {Round your answers to two decimal places.) l | min to | | min (d) Discuss the difference between part {b} and part (c). The prediction interval is much than the condence interval. This is because it is difcult to predict the waiting time for an individual customer arriving with four people in line than it is to estimate the mean waiting time for a customer arriving with four people in line. The estimated regression equation for a model involving I:wo independent variables and 10 observations follows. 1? = 21.18?0 + DEBUTXI + [1.496sz (a) Interpret 11 in this estimated regression equation. 0 bl = 0.560? is an estimate of the change in y corresponding to a I 0 bl = 0.4960 is an estimate of the change in y corresponding to a I 0 bl = 21.18?0 is an estimate of the change in y corresponding to a 0 bl = 0.5607r is an estimate of the change in y corresponding to a I 0 bl = 0.4960 is an estimate of the change in y corresponding to a f Interpret 12 in this estimated regression equation. 2 = 0.5607r is an estimate of the change in y corresponding to a I O i:- H 21.18?!) is an estimate of the change in y corresponding to a 0 112 = 0.5607r is an estimate of the change in y corresponding to a I O i:- ll 0.4960 is an estimate of the change in y corresponding to a f O t:- DJ M (b) Predict y when x E 1 = 190 and x2 = 330. unit change in x2 when x1 is held constant. unit change in x1 when )u:2 is held constant. 1 unit change in X1 when X2 is held constant. unit change in x1 when )u:2 is held constant. unit change in x2 when X1 is held constant. unit change in x1 when )u:2 is held constant. 1 unit change in x when x is held constant. 1 2 unit change in x2 when X1 is held constant. unit change in x2 when X1 is held constant. 0.4960 is an estimate of the change in y corresponding to a '_ unit change in x1 when x2 is held constant