In order to effectively implement evidence-based practice in the field of nursing, the Doctor of Nursing Practice (DNP) must possess a basic understanding of statistical measurements and how they apply within the realm of data management and analytics. This assignment will demonstrate the DNP’s understanding of basic statistical tests and their ability to perform the appropriate test for a given project using statistical software such as SPSS. The results of the inferential analysis will be utilized for decision-making rather than hypothesis testing, and it will be important to establish the necessary criterion for further implementation of the project’s findings. This paper will provide guidelines for reporting test results and emphasize the importance of real-world application in practice immersion assignments.
Developing a Conclusive Result
When reporting the results of statistical analyses, it is crucial to provide a conclusive result that adequately addresses the research question or objective of the study. This involves a careful interpretation of the data and a consideration of statistical significance. Statistical significance refers to the likelihood that the observed result did not occur by chance, but rather shows a true effect or relationship between variables.
Interpreting Statistical Significance
In order to determine the statistical significance of a finding, it is necessary to compare the observed result with a pre-determined threshold or criterion. This criterion, known as the alpha level or significance level, is typically set at 0.05 (p < 0.05), which means that there is a 5% chance of obtaining the observed result or one more extreme if there is no true effect or relationship in the population. If the p-value associated with the observed result is less than the alpha level (p < 0.05), it is considered statistically significant. This indicates that the observed result is unlikely to have occurred by chance alone, and provides evidence for the presence of a true effect or relationship. Conversely, if the p-value is greater than the alpha level (p > 0.05), the observed result is not considered statistically significant, and there is insufficient evidence to support the presence of a true effect or relationship.
Reporting Test Results
When reporting test results, it is important to adhere to certain guidelines to accurately convey the findings of the analysis. The following guidelines can be used to report the results of statistical tests:
1. State the research question or objective: Begin by clearly stating the research question or objective that the analysis is addressing. This will provide context for the interpretation of the results.
2. Describe the sample: Provide a brief description of the sample used in the analysis, including relevant characteristics such as sample size, demographics, or clinical diagnosis.
3. Report the test statistic: Inferential statistical tests generate a test statistic that summarizes the evidence for or against the null hypothesis. This test statistic, along with its degrees of freedom, should be reported.
4. State the null and alternative hypotheses: Clearly state the null hypothesis, which assumes no effect or relationship, and the alternative hypothesis, which posits the presence of an effect or relationship.
5. Provide the p-value: State the p-value associated with the test statistic. This provides an indication of the statistical significance of the observed result.
6. Interpret the result: Based on the p-value, interpret the result in the context of the research question or objective. If the p-value is less than the alpha level, report that the observed result is statistically significant. If the p-value is greater than the alpha level, report that the observed result is not statistically significant.
In summary, the DNP must have a basic understanding of statistical measurements and their application in data management and analytics. When reporting the results of statistical analyses, it is important to provide a conclusive result based on the guidelines for statistical significance. These guidelines involve interpreting the p-value, which compares the observed result with a pre-determined alpha level. Additionally, reporting the test statistic, null and alternative hypotheses, and interpreting the result accurately are crucial for effectively conveying the findings of the analysis. These guidelines should be followed to ensure successful completion of the assignment and to establish the necessary criterion for further implementation of the project’s findings in the real-world practice setting.