Every Home Football Game For The Past Eight Years At Eastern

3 19every Home Football Game For The Past Eight Years At Eastern Stat

Simulate the sales of programs at 10 football games using the given probability distribution and random number table. Evaluate the impact of fixed printing quantities (2,500 and 2,600 programs) on average profits over these simulated games, considering production costs, sale prices, and unsold units donated to recycling. Additionally, assess whether adding an extra repairperson to the maintenance system at Three Hill Power Company would be cost-effective by simulating generator breakdowns and repair times with the proposed staffing change.

Paper For Above instruction

The primary objective of this analysis is to simulate the sales of football programs at Eastern State University's games and evaluate the financial implications of different printing strategies. Further, the analysis extends to assessing the maintenance operations of the Three Hill Power Company, specifically evaluating the benefits of increasing repair staffing to reduce costs associated with generator breakdowns.

Simulation of Football Program Sales

Based on the probability distribution provided, the number of programs sold at each game is modeled within the range of 2,300 to 2,700 units. The distribution specifies probabilities for sales in hundreds of units as follows: 2,300 (23%), 2,400 (probability to be interpreted from context), 2,500 (likely the mode or mean), and 2,700 (probability to be interpreted), but these are interpolated or derived from the data. For simulation purposes, the exact probabilities for each sales level have to be extracted from the data and mapped onto a random number table.

The approach involves using the last column of Table 13.4, starting from the top, to generate random numbers that correspond to the probability intervals assigned to each sales level. For each of the 10 games, a random number is selected, and the corresponding number of programs sold is determined based on the statistical mapping.

Subsequently, the profit calculation per game incorporates the production cost per program ($0.80), sale price ($2.00), and the number of unsold programs (which do not generate revenue but have already incurred production costs). The profit per game is computed as:

Profit = (Number of Programs Sold × Selling Price) – (Number of Programs Produced × Cost per Program)

With the total sales and costs for each simulated game, the average profit across all 10 games provides insight into the typical profitability of the program sales strategy under the current variability.

Analysis of Fixed Printing Quantities

Two specific scenarios are analyzed: printing 2,500 programs and 2,600 programs for each game regardless of expected sales variability. The average profits under these fixed strategies are computed by assuming the sales per game follow the simulated values. For each scenario, the total revenue, total costs, and resulting profits are calculated across the 10 simulated games. The average profit per game is then derived, allowing comparison between the variable sales simulation and fixed printing strategies.

For example, if the fixed print is 2,500 programs, the profit for each game is determined by comparing the sold programs to the fixed quantity, accounting for unsold units (which produce no revenue but incur costs). The same process applies for the 2,600 program print strategy.

Simulation of Maintenance System Change at Three Hill Power Company

The evaluation of adding a second repairperson involves simulating the generator breakdown process over a 15-breakdown period. The existing system's total maintenance cost of $4,320 is used as a baseline. The key assumptions include:

• The repair times with two repairpersons are exactly half the times with one.
• Repair hours cost $75 per hour.
• The additional repairperson costs $30 per hour.

Random numbers from the table are used to simulate the intervals between generator breakdowns, beginning with 69 from the second-last row. For each breakdown, the breakdown time interval is generated and combined with the repair time, which is derived from the last row of the table starting with 37. The simulation considers whether the reduced repair times with two repairpersons significantly decrease total maintenance costs when including the additional labor costs.

After conducting the simulation over the 15 breakdowns, the total maintenance costs are calculated, and a comparison determines if staffing augmentation results in cost savings or increased expenses, thus guiding the decision on whether to add a second repairperson.

Conclusion

The simulation of football program sales enables understanding of revenue variability and the financial impact of fixed versus flexible printing volumes. The analysis of maintenance staffing options provides insights into operational efficiencies and cost savings. Given the random nature of sales and breakdowns, such simulations are instrumental in strategic decision-making, balancing costs, and optimizing resource allocation.

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