Assignment Help: It is important to understand that numbers are just numbers and words are just words—all data obtained from EBP projects and research data collection must be interpreted.

It is important to understand that numbers are just numbers and words are just words—all data obtained from EBP projects and research data collection must be interpreted. In other words, a project coordinator or researcher must add meaning to data. When interpreting data, a project coordinator or researcher needs to have two viewpoints: Consider what the data say and consider what the data do not say.

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With quantitative data, the interpretation would include the descriptive statistics about the sample, hypothesized data, and unhypothesized data. With qualitative research, data are reduced to common themes and/or patterns and then relationships between the common themes and/or patterns are reported.

Key to both approaches is quality—quality of the approach, sampling, methodology, and analysis. Guidelines useful in analyzing quantitative and qualitative approaches are presented in this lesson. The presented guidelines are your starting point; as you become more knowledgeable regarding the evaluation and use of research, you may want to add more criteria.

Statistical and Clinical Significance

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The difference between statistically significant results and clinical significance is very interesting. For this discussion, respond to each of the following topics.

Distinguish between statistical and clinical significance of results.
Would it be possible to have research study results that supported the acceptance of the null hypothesis and demonstrate clinical significance? Provide a hypothetical example that supports your answer.
If you question the credibility of the results from a qualitative study, would the information have clinical significance for your practice area? Why or why not? Provide a hypothetical example that supports your answer.

MODEL ANSWER

Statistical Versus Clinical Significance of Results

Statistical significance of results entails the likelihood that a given research result is real and represents the true picture of the sample size. If a given sample size is big, statistical results are significant as they show very small differences between different sample sizes. On the other hand, clinical significance provides information on how effective or important the findings of research are to a given patient. In that case, clinical significance is subjective rather than objective (Schneider, 2013).

Would it be possible to have research study results that supported the acceptance of the null hypothesis and demonstrate clinical significance?

Yes, it is possible to have instances where the null is accepted and shows clinical significance. For example, if we consider a null hypothesis that “scrubbing and drying a wound for 30 seconds and letting it dry leads to less contamination.” It can be shown that continued use of this practice can actually prove the validity of this statement.

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