Test bias does explain the consistently reported differential test performance for a number of reasons. First of all, the bias may arise from the inherent features of its design such as online distribution where the control could be exercised only partially, and the possibility of providing assistance may be limited. There is a certain possibility that certain gender, race or culture would be much more generously represented in the sample whether or not the researchers anticipated it. In these circumstances, the validity would be violated, which presents a problem of proving the initial hypothesis. Since the cultural bias could be extremely challenging to identify and eliminate, it will still continue to influence the results of the tests in non-homogenous societies.
Another point in favor of bias explaining the consistency of the test performance is that the planning stage of the test failed and the subjects were not clearly defined in the process, which, again, triggered a certain clusteredness in the results. The possible indicators of such fact could lie in the field of unclear predictions regarding the sample. The gathered homogenous results could indicate an issue of inadequate sampling, and raise a question of validity due to the assumption of the unclear sampling technique.
For instance, if the results of a survey that pursued a goal of identifying the favorite color in ‘people’ and the results showed that 85% prefer green while the respondents were mostly female, then a test could be biased in terms of its administration. It might have been that the researchers unintentionally distributed the test among the neighborhood with green-painted houses were happened to be an overwhelming percentage of women. The results of such a test would, therefore, be biased. In any case, profusely consistent research data might raise some issues of biasness and cast a shadow on the whole research, which underlines the necessity of studying and eliminating bias during the planning stage as the consequences of an error could undo large amounts of work.