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The concepts that follow focus on a personal decision of uncertainty.

""Assignment: Decision of Uncertainty Paper

· Resource: Week Three Student Roadmap (ENCLOSED)
· Research statistical data in a business context that requires a decision. Use probability concepts to formulate a decision.
· Write a 700- to 1,050-word paper, explaining your research methods and process for limiting the uncertainty in the decision. Explain the following:
· Include how you applied concepts to formulate your decision
· Include appropriate probability concepts and your application to find resulting data to limit uncertainty in this decision.
· Identify each outcome from your statistical analysis, providing rationale for each.
· Identify tradeoffs between accuracy and precision required by various probability concepts and the effect on your data.
· Include the decision you made based on statistical data.""

QNT/561 Student Road Map Week Three—Student Road Map STUDENT ROAD MAP This Road Map will help you become familiar with the expectations of this assignment and provide some direction on how to structure it. This material is an example only, as you must research statistical data to help make a business decision. The concepts that follow focus on a personal decision of uncertainty. Use these probability concepts to help guide you in structuring your assignment. Remember to present your paper as a narrative. Assignment: A Decision of Uncertainty Research statistical data within a business context that requires a decision to be made. Then, use probability on your researched data to formulate a decision. Write a 700- to 1,050-word paper in APA format explaining your research methods and process for limiting the uncertainty within the decision. Discuss your results in an in-depth narrative. Be sure to explain the following in your paper: o How you applied the concepts from the example scenario to formulate your business decision of uncertainty. o The appropriate probability concepts and your application of them to find resulting data to limit the uncertainty within this business decision. o Identification of each discrete outcome from your statistical analysis, providing statistical rationale for each. o The trade-offs between accuracy and precision required by the use of various probability concepts, and the effect on your data. Example Scenario Decision: To buy or not to buy cruise insurance I decided to take a cruise this year. However, due to money and work constraints, the cruise was to be taken during the month of October. Through my research and compliance with my constraints, the most opportune time to travel
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on a cruise was during the week of October 8 – 14. However, according to the weather bureau, this particular week was the height of hurricane season. According to the cruise line, if a cruise is cancelled due to a hurricane there is no refund. However, for a 30% fee hurricane insurance can be purchased to ensure one can expect their money back if the cruise is cancelled, except for the fee of course. I have to decide whether to book the cruise and not worry about hurricanes; thus risk losing my vacation fund, or book the cruise and pay extra for the hurricane insurance, which subsequently adds more to my spending and stresses the allocated budget for this vacation. Research To make an accurate decision, I researched my trip. My researched data set was from the National Oceanographic and Atmospheric Administration (NOAA) and consisted of weather condition statistics over the past 10 years. More importantly, my research specified the date and duration of hurricanes. Since my trip was to take place during the week of October 8 – 14, my research primarily concentrated on this time frame. Once the research was gathered, I focused on accurately interpreting my data to make an accurate decision. Interpretation of Data (using Bayes’ Theorem) To interpret my data, I chose to use Bayes’ theorem as the probability model that was the most applicable to my vacation decision. Bayes’ theorem emulates the process of logical inference by determining the degree of confidence in possible conclusions based on the available evidence. This evidence is best stated in terms of subjective probability, where the probability is based on evaluating opinions and information, then estimating this data and finally assigning probability to the outcomes. Therefore, Bayes’ theorem is best used for the purposes of predicting confidence levels for purchasing hurricane insurance, predicting the occurrence of a hurricane, and or predicting a captain’s cancellation notice if there is said hurricane. While there are other effective analytical tools used to derive the probability of data, i.e. hypothesis testing, Bayes’ theorem is more appropriate for this situation based on the subjective nature of the evidence. Part of statistical modeling is using the right analytical tool for the appropriate situation. Hypothesis testing is more effective for a scenario with an observed difference. In other words, hypothesis testing is used to determine the probability when a given hypothesis is true. In our cruise scenario, for example, hypothesis testing could be used if one professional body said the probability of a hurricane being present is .5,
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