In statistics, there are inferential statistics and descriptive statistics. Descriptive statistics is used to summarize without drawing conclusions about the statistics at hand (Kaliyadan & Kulkarni, 2019). Descriptive statistics uses graphs and charts to help understand the statistics’ central tendency, distribution, and dispersion or variability (Stacey Beth Plichta & Kelvin, 2015). In clinical practice, using all three is important for displaying data and improving patient outcomes and knowledge for the staff. Central tendencies are listed along with graphs, scatter plots, and pie charts that display the statistics’ distribution and dispersion or variability. The most commonly seen in clinical practice is measuring central tendency, specifically using the mean or average (Conner & Johnson, 2017). For example, the average number of patient populations is tracked. Applying dispersion and variability allows the researcher to see the outliers and the data spread. It is important to understand how to apply descriptive statistics in clinical practice. This is utilized in quality improvement projects that nurses are often asked to lead or understand. Applying evidence-based practice protects patients and ensures the highest quality of care is given.

References

Conner, B., & Johnson, E. (2017). Descriptive statistics Use these tools to analyze data vital to practice-improvement projects. American Nurse Today, 12(11).

Kaliyadan, F., & Kulkarni, V. (2019). Types of variables, Descriptive statistics, and Sample Size. Indian Dermatology Online Journal, 10(1), 82–86. ncbi. https://doi.org/10.4103/idoj.IDOJ_468_18

Stacey Beth Plichta, & Kelvin, E. A. (2015). Munro’s statistical methods for health care research (6th ed.). W. Ross Macdonald School Resource Services Library.

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