# The Times–Divide Expression: An Intuitive Approach for Describing Right-Skewed Data in Nursing Practice

## TL;DR

This paper introduces a new statistical method for handling skewed nursing data, improving clarity and decision-making in clinical settings.

## Contribution

The paper introduces the times–divide expression (GMean ×/GSD) as a novel approach for describing right-skewed nursing data.

## Key findings

- The times–divide expression better represents skewed nursing data than traditional mean ± SD.
- It provides clearer distributional insights and percentile ranges for clinical decision-making.
- Application of the method is shown to enhance data interpretation in nursing practice.

## Abstract

In clinical nursing practice, it is crucial to share data overviews simply and intuitively with all team members. Descriptive statistics, typically expressed as the arithmetic mean plus–minus the standard deviation (Mean ± SD), are commonly used for this purpose. However, this approach is inadequate for describing asymmetric, right-skewed distributions, commonly encountered in nursing. This study introduces an alternative—the times–divide expression (GMean ×/GSD)—based on the geometric mean and geometric standard deviation. We present a data-driven study that examines the applicability of this expression using nursing demand data collected over four and a half years from a nurse call system. The results indicate that the times–divide expression outperforms conventional methods in representing distributional properties and providing suitable representative values and usable percentile range indicators. Applying the times–divide expression to the actual distribution of data is expected to improve nurses' clinical decision-making skills through data-driven insights, ultimately enhancing the quality of care.