Think of and share a research scenario in the area of leadership where the use of P values would be use. Identify the independent and dependent variables and explain the use of P scores would be appropriate.

Example

Scenario Expressing the Importance of P-Values

In this scenario, we will look at the leadership styles of a culinary leader and its effect on turnover rates.  The classic sense of a chef, that is amplified by food based television programs is one who’s leadership style is a dictatorial style.  This reaches back to the start of the European kitchen, where the kitchen was operated like a military operation, with a direct management style (Escoffier On Line, 2007).  In the United States, today, labor regulations prohibit or severely limited this style of leadership, but there are many who still employ this style.  This style has a large impact on the turnover rate in culinary operations today, which is slowly pushing towards other leadership styles to manage the operation. This study is positioned to show the direct correlation between the turnover rate and leadership style.

            In this scenario, the independent variable would be the leadership style of the culinary leader.  The dependent variable would be the turnover rate of the culinary operation.  These two variables would lead to the hypothesis (H1) that a positively motivated culinary leader would have a positive impact of lowering the turnover rate in the operation.  The null hypothesis (H0) would be that the leadership style of a culinary leader has no impact on the turnover rate of the organization.  The alternative hypothesis would be that there is a significant relationship between the two variables of leadership and turnover.

            The p-scores in the above scenario would allow us to predict the likelihood that a score would occur in this case a predicator of the relationship.  In a large population, the p-scores that are above .05, this would have the probability of this event occurring.  Below a .05 p-score, then there is a low chance of this event occurring.  These p-scores would allow us to visit and assess the probability of the hypothesis being true, as well as assessing data that might be outside the norm.