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Before describing the implication of diversity in doing research, it is important to note that any research should be as specific as possible. For example, suppose the researcher intends to evaluate or find out whether women experience more automobile accidents than men, then the researcher should specify the variables to be used. Too many variables may make the study too general and invalid. One researcher may opt to approach this research by comparing women and men in terms of how easily they get distracted and the number of accidents they face either gender. Another researcher may opt to just approach this research by analyzing accident cases and counting which of the cases is caused by women and which is caused by men. The two researchers would have different survey questions.
The first researcher will have a relatively diverse survey questions because he or she is considering two variables, whereas the latter researcher will have homogenous survey questions (Jackson, 2012). When the variable survey questions are diverse, the significance and mean of the variables may be skewed to the right or left depending on the degree of diversity. If some of the values in the variables are extremely low, then the mean would be lower than the median and hence the results will be skewed to the right. Alternatively, if the diversity is made up of variables that are extremely high in value, then the mean will be more than the median and the results will be skewed to the left. Skewness may distort the true meaning of the results (Jackson, 2012).
Consequently, the researcher needs to take into account a number of aspects. The first aspect is outliers. The researcher should remove any outlier as possible because it is the outliers that are responsible for the shift of the results (Jackson, 2012). In addition, the researcher should make the survey questions relatively specific.
Jackson, S. L. (2012). Research methods and statistics: A critical thinking approach. Belmont, CA: Wadsworth Cengage Learning.