Reduction of bias through Analysis of Competing Hypotheses

Reduction of bias through Analysis of Competing Hypotheses

Reduction of bias through Analysis of Competing Hypotheses

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Analysis of competing hypotheses (ACH) is one of the tools that a research can use to arrive at a sound judgment about hypothesis. This is because it is a tool that requires one to clearly identify all the rational options and then weigh them out instead of examining their credibility individually. The first step of the process is to identify all hypotheses which are relevant and should be examined (Heuer, 2008). This step allows the research to formulate hypothesis using different perspectives and backgrounds. All potential possibilities are examined before any hypotheses are ruled out. Premature rejection of unproven hypothesis which have not been disapproved would bias analysis.

In the second step a list of important verification and arguments for and against the various hypotheses is made (Heuer, 2008). This allows the research not to overlook anything by being comprehensive. The third step involves taking the hypotheses created and the evidence gathered and putting this information in a matrix (Heuer, 2008). The research thus gets an overview to the problem under analysis. Here evidence is not examined against how well it supports a hypotheses but rather how it relates to all the hypotheses.

Step four is the re-examination of hypotheses so that they can be better suited for more analysis and the re-examination of evidence (Heuer, 2008). By getting rid of evidence with no value to the analysis, the research is made sharper and concentration is given to the relevant material. In step five the research evaluates the likelihood of alternative hypotheses. Hypotheses that are not supported by evidence are rejected while those that can not be refuted are retained (Heuer, 2008). This allows the research to retain all hypotheses that can still be proved. Through the process of re-examining evidence and hypotheses mistakes and omissions that were made can be corrected.

In the sixth step the research questions the key pieces of evidence and assumptions with great bearing on the outcome of the analysis (Heuer, 2008). This also allows for alternative explanations and the reliability of the evidence to be confirmed. In step seven, since analytical judgments remain never certain, the research presents the comparative likelihood of the alternative possibilities found (Heuer, 2008). This means that no hypothesis is left out at the expense of another. In the last step the research outlines factors that would change the reached and thus it becomes sound and open to new information (Heuer, 2008).

Analytical fallacies

During analysis, fallacies can occur and mar the outcome of the analysis. This can even lead to errors in the analysis. It is therefore important to reduce fallacies in order to achieve the best possible outcome that can be relied on. Some of the fallacies can be easily corrected while some are harder to correct.

One of the fallacies is using information that is insufficient. When sufficient information is not used the wrong conclusions can be drawn. This is one of the fallacies that can be easily corrected by supplying sufficient information or acknowledging the limitation of the information in the analysis (Heuer, 2008). Another fallacy occurs when people use consistency to formulate explanations which include the most amount of evidence in a reasonably consistent situation without examining the basis of the consistency (Heuer, 2008). Sometimes the consistency is there because information used is redundant or because the sample is limited or simply biased (Heuer, 2008). Conclusions reached thus do not make reliable representation of the subjects of analysis. By examining the evidence against all hypothesis fallacy can be removed.

Another fallacy lies in the information used. Sometimes information and data used is inaccurate, biased, distorted and thus unreliable (Heuer, 2008). This leads to unreliability. An analysis may depend much on information that they believe to be true while in essence it is not. By re-examining information analysts can judge its validity and if possible go back to the sources for accurate information.  Another of the fallacies is availability rule. Here availability means retrievability or imaginability so that people use these to judge an event (Heuer, 2008).  People however can be easily misled when other factors unrelated to the event are factored in. By using availability to judge events the wrong conclusions can be reached. This is however more correctable since facts can be introduced to the analysis to limit personal perceptions.

Another fallacy is anchoring. Here a natural starting point, which could be from prior analysis, becomes the first estimate to the preferred judgment (Heuer, 2008).  This can be corrected by adhering to the evidence and facts in their own right and being aware of the fallacy. If evidence and facts are properly followed, the outcome can be independent of this fallacy. Another fallacy occurs when numerical data used as a base rate is ignored when it does not elucidate a causal relationship (Heuer, 2008). Analysis can therefore eliminate the use of prior probability since it may not seem relevant and yet it has a bearing on the analysis. Using the analytical tools analysis increases objectivity.

Another fallacy is that impressions sometimes remain even when evidence which led to the impressions has been disapproved (Heuer, 2008). It is hard to correct since even new information does not guarantee that people will change their perceptions. Thus the fallacy can remain and compromise analysis process. Closely related to this is the fallacy where people have an inclination to opt for causal explanations. People tend to arrange information and data in ways that show relationships and form patterns (Heuer, 2008). New information may thus be manipulated to fit into understandable order of things. This fallacy is not easily corrected since people may not even be aware of it. However using methods that are objective can reduce the likelihood of them occurring.

Another related fallacy is that of seeing the actions of other people or groups the direct result of their main direction and goal of planning (Heuer, 2008). As a result incorrect judgment is made. This fallacy leaves little room for accidents and coincident. This fallacy is hard to correct as using the analytical tools does not guarantee objectivity.

References

Heuer, R. J. Jr. (2008). Tools for Thinking. Retrieved on 5th August, 20910, from

https://www.cia.gov/library/center-for-the-study-of-intelligence/csi-publications/books-and-monographs/psychology-of-intelligence-analysis/

 



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