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The connection between Promotional Status and Gender
In order to find out if the connection between promotion and gender exists, the assistant chief can design two hypotheses. The null hypothesis will tend to prove that these two dimensions are independent while the alternative hypothesis will be focused on the dependence between promotion status and gender of applicants.
According to the information mentioned in the case study, the p-value is 0.054919 (Chegg, 2016). This value is more than the significance level of 0.05 or 0.01. Thus, it can be claimed that the null hypothesis cannot be rejected, which presupposes the independence of the promotion status and gender of the applicants (Frost, 2015). As a result, there is no necessity to discuss the alternative hypothesis because it is automatically rejected. It can be concluded that the recent promotion of professionals who work at the local fire department was not affected by gender bias.
Reasons for Justifying the Absence of Gender Bias
Of course, it is not enough for the assistant chief to provide the outcomes of the case only if one is willing to ensure the chief that the promotion was not affected by any gender biases. It is critical for the professional to justify one’s conclusion and prove that he is able to work with promotions efficiently. First of all, one should present the chi-squared test that deals with the independence between the promotion status and gender of the applicants to prove that no bias occurred.
After that, the assistance chief can show the senior the ratios of promotion. In this framework, he can pay attention to the ratios of male and female employees who received promotion separately. Further, he can refer to the ratios of male and female firefighters who obtained promotion in comparison to all workers who applied for higher positions. The bias can be proved if the results show that the higher percentage of the accepted applications belong to the representatives of the particular gender (Sharpe, DeVeaux, & Velleman, 2016).
Gender Bias Impact on the Fire Department
If eventually, the assistant chief realizes that the promotion was affected by gender bias, one can expect further complications. Unequal employment opportunities will lead to employee dissatisfaction and women will not be motivated to work hard to enhance their positions.
References
Chegg. (2016). Scenario Analysis: Promotion. Web.
Frost, J. (2015). Understanding hypothesis tests: Significance levels (alpha) and p values in statistics.
Sharpe, N., DeVeaux, R., & Velleman, P. (2016). Business statistics. Harlow UK: Pearson.
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