Decision of Uncertainty

Is Rental Insurance A Good Deal?

QNT/561

April 23, 2012

Subhendu Roy

In the dynamic society knowledge is always incomplete, yet a decision must be made. “Decision making is a process of first diverging to explore the possibilities and then converging on a solution(s)" (Cooper & Schindler, 2011). Many decisions are made under uncertainty; that is, with limited information about their potential consequences. The outcome can vary greatly. Most of time uncertainty exists whenever people determine a decision on a daily basis. A decision to buy rental car insurance will be answered by using the concept of probability. This paper will focus on the application of various probabilities to formulate the decision under uncertainty. Discreet outcome from statistical analysis as well as trade-offs between accuracy and precision obtained by different probabilities concepts shall be evaluated.

According to car accident statistic stats, auto, fatal, and drunk driving, the estimation of having an accident is of one in 16 cars. It has provided useful information to make important decision. There are a number of probability concepts that can be used in determining the results from the research data that was given. Probability is used to limit the uncertainty of the decision on whether to buy the rental car insurance. The probability concept that works the best and meets all of the criteria from the information that was gathered is the Bayes’ Theorem. The application of Bayes' theorem helps to interpret the data because it is most relevant to the itinerancy of the whole trip. The Bayes' theorems follow the method of logical inference by establishing the degree of assurance in every decision (Lind, Marchal & Wathen, 2008). Consequently, Bayes' theorem is best utilized for the purpose of predicting confidence levels for purchasing rental car insurance based on the probability of getting an accident.

Despite the fact that there are other efficient analytical tools...