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Simulation Modeling

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Every home football game for the past eight years at Eastern State University has been sold out. The revenues from ticket sales are significant, but the sale of food, beverages, and souvenirs has contributed greatly to the overall profitability of the football program. One particular souvenir is the football program for each game. The number of programs sold at each game is described by the following probability distribution:

Number (in 100s) of Programs Sold Probability
23 0.15
24 0.22
25 0.24
26 0.21
27 0.18

Historically, Eastern has never sold fewer than 2,300 programs or more than 2,700 programs at one game. Each program costs $0.80 to produce and sells for $2.00. Any programs that are not sold are donated to
a recycling center and do not produce any revenue.
(a) Simulate the sales of programs at 10 football games. Use the last column in the random number table (Table 14.4) and begin at the top of the column.
(b) If the university decided to print 2,500 programs for each game, what would the average profits be for the 10 games simulated in part (a)?
(c) If the university decided to print 2,600 programs for each game, what would the average profits be for the 10 games simulated in part (a)?

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Solution Summary

Simulation model programs are examined.

See Also This Related BrainMass Solution

Mathematics - Modelling and Simulation - Model the Data

The U.S. Bureau of Public Roads determined the following characteristic total stopping distances D depending on the velocity of cars.
Speed M.P.H. (v) 20 30 40 50 60 70 80
Total Stop Distance D (ft) 42 73.5 116 173 248 343 464

a) Determine the best way to model the data. For example, by: a power function, an exponential function, or a polynomial. You may find it helpful to plot Ln(D) against both Ln(v) and v to see whether the data can be modeled by a power function or an exponential function.
b) Determine appropriate parameters for the model type chosen.
c) Calculate the relative error of your model.
d) Use the model to derive a simple formula for approximating the total stopping distance without a calculator. Illustrate the use of this formula by three examples.

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