An organization is expenencing a high level of daily absente - SHRM-SCP Practice Questions

Explanation.

The correct answer is B.

Let's break down why using a simple mean to determine causes of absence in this scenario is least effective:

1. 1. Complexity of the data:
      The data provided includes multiple categories of absences with varying frequencies and durations. A simple mean would oversimplify this complex information.
   2. Loss of important details:
      Using a simple mean would obscure crucial details such as the difference between one-day and multiple-day absences, which could be significant for understanding patterns and developing targeted solutions.
   3. Unequal weighting of causes:
      A simple mean would not accurately represent the relative importance of each cause. For instance, it wouldn't highlight that family illness and personal illness are the primary causes of absence.
   4. Inability to show patterns:
      A mean wouldn't reveal any temporal patterns or trends in the absences, which could be important for addressing the issue effectively.
   5. Misrepresentation of data:
      Given the wide range of absence causes and their varying frequencies, a mean could be skewed by outliers or less common causes.

Why the other options are incorrect:

A. "One method that is always reliable" - This is incorrect because the reliability and effectiveness of a statistical method depend on the nature of the data and the specific questions being addressed.

C. "Most effective" - As explained above, a simple mean would be one of the least effective methods for analyzing this complex data set.

D. "Too difficult to calculate" - While this is not correct (a mean is generally simple to calculate), it's also not relevant to the effectiveness of the method.

More effective methods for analyzing this data might include:

• • Calculating percentages for each cause of absence
  • Using visual representations like pie charts or bar graphs
  • Analyzing patterns in one-day vs. multiple-day absences
  • Examining trends over time if temporal data is available

These methods would provide a more comprehensive and nuanced understanding of the absenteeism issue, allowing for more targeted and effective recommendations to the leadership team.