In a company, the decision-making process is crucial. The progress and success of the company are determined by the types of decisions made, depending on the set goals (Pownall, 2019). The managers play a vital role in the process and even providing platforms for other workers in the organization to solely participate. In the process, errors might occur. However, the errors are divided into two major categories: False-positive vs. a false negative, also known as type I and type II errors respectively. The two have impacts on the decision-making process and the general company’s operations. Thus, it is as good as gold to understand both of them. In the paper, scrupulousness will be focused on comparing and contrasting the two.
In binary classification, false-positive occurs where, after a study or a test is conducted, the results come out indicating the presence of what is expected (Stoian, 2016). In this scenario, the outcome posted shows the positivity. It should be clear that these are errors. This type of error provides hope to an individual or cooperation. For instance, the organization may intend to conduct an internal audit following the litigation. In the auditing process, the auditor may decide to deceive the company by providing results that litigation can not happen and the company is in safe conditions whereas, in reality, the company faces the threat. On the other hand, the false-negative error occurs where the results indicate the presence of a condition but they are lied to make the condition not to exist. For instance, in a company, which is facing the threat of litigation, the auditor may decide to post that it is true the company is facing the problem but the reality is it is not.
False-positive and false-negative are both errors. They all indicate the opposite of what the reality is (Stoian, 2016). In statistics, they all emerge from statistical hypothesis testing. During the testing, the conclusion arrives. The conclusion is not right, which results in an error. However, depending on the conclusion and error posted, the type of error is determined, which is the type I or type II. Furthermore, both have consequences (Stoian, 2016). Baring in mind that all type I and type II are all false, therefore the consequences are to be expected. It should be noted that both occur due to reasons. At least, the one providing the errors should have the best reason out to why he decides to do so. To some extent, it happens depending on the situation the person is or the organization is. For instance, if the auditor finds out that if he tells the truth the company may collapse, the alternative of deploying either the two will save the existence of the company though in straggles. In another example, HIV vaccine trials use negative patients. In the study, the patients understand that they are positive but in reality, they are not.
The two types of errors have differences. The differences exist in terms of repercussions each brings out (Pourmorteza, 2016). In a company, which is conducting an audit due to the loss of funds the auditor may post either a false positive test or false-negative test. The results haunt the companies operation. For the case of the false positive, the company will take a measure that will cost it much. For instance, the organization may decide to embark on the means of how to find out the frauds of the company’s money. Detectives and other agents may be deployed to ensure the culprits are gotten and subjected to the law. On the other hand, if it is said that there is no corruption, the company may suffer a lot in terms of funds to run it. This means that there will be no restrictions on the funds being used in the company, even though some are lost. Therefore, the two have consequences that vary. At least the worst must be encountered between the two. This means that it is better if the reality is shade rather than the errors, maybe to entice a certain party.
With the understanding of the two types of errors, it is vivid that they have impacts on the company. It should be clear that it is not always that the errors are intentional. Sometimes they occur unintentionally, for instance in statistical tests. Basing on the knowledge, the two can have a positive impact or a negative impact on the company. Depending on the type of error, the company may impart in more effort to ensure it reverts to normality and progress. For instance, in a test of corruption in the company, if the result may show that the company had been facing corruption whereas in the real sense there is no corruption, the organization will strive to finish all the possible loopholes that may result in money lost. This is a good take since it will improve the security of the firm.
However, false positive and false negative can also affect negatively the company. With the same illustration of corruption, the organization may tend to set up measures that will ensure the offenders are identified. This consumes a lot of many hence going to waste. It is therefore clear that type I and type II errors affect the decision making. The decision is made according to the results. If the results have errors, the decision made by the company may also have negative effects on the operations since it is applied when it is not to be applied (Pownall, 2019).
Pourmorteza, M., Bansal, A., Chaudhari, D., & Young, M. (2016). PPI and False-positive THC Screen: False Positive Equal False Allegation: 2331. American Journal of Gastroenterology, 111, S1134.
Pownall, I., Kennedy, V., & Acquaye, D. (2019). Do new first-year students seek optimal distinctiveness in a new learning environment?. The International Journal of Management Education, 17(2), 254-266.
Stoian, D., Craciunescu, M., Craina, M., Pantea, S., & Varcus, F. (2016). False-negative results of real-time strain elastography in thyroid nodular disease. Ultraschall in der Medizin-European Journal of Ultrasound, 37(S 01), PS4_03.
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