A doctoral student is surveying chief executive officers (CEOs) to understand their levels of satisfaction with work-life balance over a period of three years. The student receives responses to survey with a question regarding how many hours a week each CEO works. Which statistical approach should be used to display the data for analysis?

While the mean provides a measure of central tendency for the hours worked, it does not convey the distribution or relationship between hours worked and satisfaction levels. The mean alone may not be sufficient to capture the complexity of the data over the three-year period, particularly if it includes outliers.

A bell curve, or normal distribution, is a theoretical model used to describe the distribution of data, but it does not serve as a tool for displaying individual data points or relationships between variables. It would be inappropriate for the analysis of survey responses from multiple CEOs, which may not conform to a normal distribution.

The median represents the middle value in a dataset and can indicate central tendency effectively; however, it does not illustrate the variability or relationships present in the data. In this context, relying solely on the median would overlook valuable insights gained from examining the distribution of hours worked alongside satisfaction levels.