# Example Of Course Work On The Use Of Heuristics In Making Judgments

Published: 2021-07-10 00:05:04

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Heuristics is the use of guides to make decisions or to make solutions of any issues at hand (Hasite 2010). The problem solving made by the use of heuristics is usually based on experience. Many analysts have argued that the use of heuristics has enabled problems to be solved more promptly and also faster. The use of this phenomenon may involve the use of common sense as well as the use of thumbs. There are two major types of heuristics; availability and representativeness. This research paper will focus on the advantages and disadvantages of heuristics as an approach of solving problems. In addition, the research paper will compare and contrast availability heuristics and representative heuristics.
The availability heuristics is a concept that involves the prediction of the occurrence of an event based on other events that have ever occurred before. On the other hand, representativeness heuristics is the prediction of the occurrence of an event based on the resemblance of the phenomenon with data (Daniel, 2005).

One example of the representativeness heuristics involves the use of probabilities to predict the actual events that had occurred (Daniel 2005). In a certain period of time, there was an accident involving two cabs. In that place, cabs were of only two colors. One of the colors was blue, whose probability was 0.15 while the other one was green, and whose probability was 0.85. A witness was therefore required to tell which of the colors represented the cab that had hit the other. According to him, the cab was blue in color (Pearl, 2006). However, the court used the concept of probability to evaluate whether there was a high probability that the witness had chosen the actual suspect. An example of availability heuristics is based on the occurrence of earlier events. For instance, a person may argue that his relative has smoked cigarette for many years and has never been ill of cancer. Although this is based on past experience, it may however not apply to everyone.

One similarity of representativeness heuristics and availability heuristics is that they are both used to give solutions to problems. The other similarity is that they are important phenomena for making judgments in our day to day lives (Pearl 2006). One difference between them is that availability heuristics involves the use of imagination to come up with outcomes, unlike representativeness heuristics. The other difference is that representativeness heuristics involves resemblance of data that is available in order to make judgments, unlike availability heuristics.

Based on the comparison of the two types of heuristics, one would argue that both of them are important in making judgments. From this comparison, the use of representativeness heuristics is more accurate than the use of availability heuristics. This is merely based on the fact that the past occurrence of events is not an assurance that these events will occur in the same way in the future. One advantage of heuristics is that it is generally cheap and does not involve a great deal of planning. One of its disadvantages is that difficult and complex solutions cannot be solved by some forms of heuristics like educated guess (Pearl, 2006). Finally, based on the past use of heuristics, this phenomenon has helped a lot to solve problems in our society. That is the major reason why people should continue using it as a way of making prompt judgments.

In conclusion, heuristics is a very important approach in solving problems. It facilitates solving problems at a faster rate as compared to other approaches. Even though there are differences in the two types of heuristics both are very important in solving problems.

References

Hasite, R, (2010). Rational choice in an uncertain world: The psychology of judgment and decision making. Sage.
Daniel K, (2005) Judgment under Uncertainty: Heuristics & Biases. Cambridge. Cambridge University Press.
Pearl, J, (2006). Heuristics: Intelligent Search Strategies for Computer Problem Solving. New York. Addison-Wesley.

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