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Statistics is used to prove or disprove a question of probability, typically using the scientific method in order to determine if a hypothesis can be accepted or rejected. According to Page (2014), “Statistical significance is based on assumptions and the sample tested should be representative of the entire clinical population.”

On the other hand, clinical researchers as well as clinicians must concentrate on clinically significant changes, even though clinical significance is really not at all well-defined or understood for that matter. Unfortunately, statistically significant outcomes are often mistaken for clinical relevance. Effect size is one of the most important indicators of clinical significance, reflecting the magnitude of the difference in outcomes between groups (experimental and control) (Page, 2014). Clinically relevant measures, such as effect size, meaningful differences, etc. should be taken into consideration when interpreting and implementing results of evidence-based approaches to clinical decision making.

Practical clinical significance answers the question, how effective is the intervention or treatment, or how much change does the treatment causes. Therefore, I would use clinical significance by assessing the effectiveness of medication and assessing the correlation between independent and dependent variables to asses if the pre-test and post-test have any positive results to the overall treatment and prevention of UTIs.