Expected values of $2.54 million and $2.53 million leave the choice open, so this MT445 Unit 9 analysis picks between two ferry designs on regret and information value. Searches like "mt 445 unit 9 assignment example", "mt445 unit 9 sample" and "mt445 unit 9 example" land here.
What a finished MT445 Unit 9 expected value analysis looks like
Three tables carry roughly six pages. The payoff table gives each boat's 20-year net present value, purchase price included, under three resort outcomes weighted 0.5 on time, 0.3 delayed two years and 0.2 canceled. The like-for-like boat returns $1.9 million, $1.5 million and $1.2 million; the 300-seat walk-on design $3.7 million, $2.1 million and $0.3 million; the car-deck design $4.6 million, $1.7 million and a $1.4 million loss. Expected values follow at $1.64 million, $2.54 million and $2.53 million. The regret table subtracts each payoff from the best available in that outcome, giving maximum regrets of $2.7 million, $0.9 million and $2.6 million. A third table computes the expected value of perfect information, $630,000, and a line chart shows the car-deck boat pulling ahead once an on-time opening passes about 51 percent.
How a MT445 Unit 9 example is structured
Probabilities are sourced before they are used: the resort's permits are issued, its construction loan has not closed, and the 0.5, 0.3 and 0.2 weights are the owners' judgment after a meeting with the developer, labeled as such. Payoffs come from a stated model of riders and fares for each boat over 20 years, so every cell can be traced. Expected value is computed first and found nearly silent, a $10,000 gap on $2.5 million. Attention then shifts to what each choice risks, and the regret table shows the car-deck boat's $2.6 million exposure if the resort is canceled beside the walk-on boat's $900,000 worst case. Perfect information would be worth $630,000, which caps what any delay could be worth. The recommendation follows: the 300-seat walk-on design, with a paid five-month hold on the shipyard slot until the loan closes.
Where the probabilities come from
Issued permits, an unclosed construction loan and the developer's own schedule inform the 0.5, 0.3 and 0.2 weights. The paper labels them as the owners' judgment rather than measured frequencies.
Nine payoffs, one table
Each boat's 20-year net present value appears under each resort outcome, from a $4.6 million best case for the car-deck design to its $1.4 million loss if the resort is canceled.
Expected values that barely differ
Weighted averages come to $1.64 million, $2.54 million and $2.53 million. On this measure the two larger boats are tied, the paper says plainly, and the tie decides nothing.
What each choice risks
Measured against the best boat in each outcome, the walk-on design never trails by more than $900,000. The car-deck design can trail by $2.6 million, and the like-for-like hull by $2.7 million.
Six hundred thirty thousand as a ceiling
Perfect knowledge of the resort's fate would raise expected value from $2.54 million to $3.17 million. The paper uses that $630,000 to justify paying for a five-month shipyard hold.
Where marks go in MT445 Unit 9
Weighted averages computed correctly and then ranked as if a $10,000 gap on $2.5 million settled anything are the pattern instructors mark down most in this unit. They usually want the spread of outcomes and the price of a wrong call inside the decision. Probabilities offered without a source, or summing to something other than one, undermine every figure that follows. Regret tables built against the wrong benchmark, each option's own best case rather than the best option in each state, recur often. The value of perfect information is frequently misread as a sum worth paying for a forecast; it is a ceiling, and the stronger paper uses it to price a concrete delay. Recommendations silent on attitude to risk, when one option can lose $1.4 million, read as incomplete under most rubrics.
Get a MT445 Unit 9 example written to your instructions
List the options your Unit 9 decision offers, the outcomes that could follow and any probabilities supplied, then add the rubric. A sample with the payoff table, expected values, a regret table and the value of perfect information worked in the open comes back within 24-48h. First samples cost nothing, and assumed probabilities are labeled as assumptions.
MT445 Unit 9 questions, answered
What is the expected value of perfect information?
It is the most a decision maker should pay to learn which outcome will occur before choosing. Compute the expected payoff if you could always pick the best option for each outcome, then subtract the best expected value available without that knowledge. The result is a ceiling: real forecasts are imperfect, so any study or delay is worth less.
Should the recommendation always follow the highest expected value?
Not always. Expected value suits decisions repeated many times or small relative to the firm. For a large one-off choice the spread of outcomes matters, and a firm that could not absorb the worst case may reasonably prefer a slightly lower expected value with less downside. Say which view your recommendation takes and why.
How do I build a regret table?
For each outcome, find the best payoff any option achieves, then subtract each option's payoff from it. The differences are regrets, the cost of having chosen that option once the outcome is known. Summarize each option by its maximum regret, its expected regret or both, and note that minimizing expected regret picks the same option as maximizing expected value.