Vehicles heading west on Front Street may turn right, left, or go straight ahead at Elm Street...

Vehicles heading west on Front Street may turn right, left, or go straight ahead at Elm Street. The city traffic engineer believes that half of the vehicles will continue straight through the intersection. Of the remaining half, equal proportions will turn right and left. Two hundred vehicles were observed, with the following results. Can we conclude that the traffic engineer is correct? Use the 0.10 significance level. Please show all work and answers in excel format.

Queue discipline & simulation

1) A goal of many waiting line problems is to help a firm find the ideal level of services that minimize the cost of waiting and the cost of providing the service. True or False 2) One difficulty in waiting line analysis is that it is sometimes difficult to place a value on customer waiting time. True or False 3) An "infinite calling population" occurs when the likelihood of a new arrival does not depend on the number of past arrivals. True or False 4) The term queue discipline describes the A degree to which members of the queue renege. B sequence in which members of the queue arrived. C degree to which members of the queue are orderly and qui... click for more

CoffeeTime is considering selling juices along with its other products.

CoffeeTime is considering selling juices along with its other products. States of Nature High Sales Med. Sales Low Sales A(0.2) B(0.5) C(0.3) A1 (sell juices) 3000 2000 -6000 A2 (don't sell juices) 0 0 0 The probabilities shown above represent the states of nature and the decision maker's (e.g., manager) degree of uncertainties and personal judgment on the occurrence of each state. What is the expected payoff for actions A1 and A2 above? What would be your recommendation? Interpret the results based on practical considerations. b. Bayes and empirical Bayes (EB) methods structure combining information from similar components of information and produce efficient inferences ... click for more

Laura wanted to build a multiple regression model based on advertising expenditures and coffee times price index. Based on the selection of all normal values she obtained the following:

Laura wanted to build a multiple regression model based on advertising expenditures and coffee times price index. Based on the selection of all normal values she obtained the following: 1) Multiple R = 0.738 2) R-square = 0.546 By using lagged values she came up with the following: 3) Multiple R = 0.755 4) R-square = 0.570 Explain the differences in using these different models. How could CoffeeTime further optimize this model? b. Tourism is one consideration for CoffeeTime's future. A survey of 1,233 visitors to Mumbai last year revealed that 110 visited a small café during their visit. Laura claims that 10% of tourists will include a visit to a café. Use a 0.05 significance le... click for more

Multiple regression model

a. Laura wanted to build a multiple regression model based on advertising expenditures and coffee times price index. Based on the selection of all normal values she obtained the following: 1) Multiple R = 0.738 2) R-square = 0.546 By using lagged values she came up with the following: 3) Multiple R = 0.755 4) R-square = 0.570 Explain the differences in using these different models. How could CoffeeTime further optimize this model?