Descriptive analysis (statistics) as Houser (2019) mentioned is a research designed to describe in detail a process, event, or outcome. This is used when a there is little known about the research question. I learned this is the first step in which it is important for completion. The importance is to provide basic information of how variables are alike or different. The studies may be performed through numerical or graphical methods to enhance understanding and must be presented to meaningful to allow readers to comprehend. The most common of this analysis is expressed as measures of mean, median, mode, percentile ranks, standardized scores, bar chart, line graphs, and plot charts.

DeCaro (2003) described Inferential analysis as the statistical test to determine if the results of the sample are representative of a large population. I learned that the hypotheses is tested instead so a conclusion can be drawn, which differentiates from descriptive which summarizes. Inferential analysis also samples naturally which can lead to a sampling error which then means a sample is not expected to represent the population perfectly. The methods here are the estimation of parameters and the testing of statistical hypotheses.

Qualitative analysis is a natural approach to research that focuses on the meaning from the individual’s experience. I learned that this analysis focuses more on numbers and uses subjective judgment based on unquantifiable information. Since this analysis involves inexact information it can be difficult to collect and measure.

Data analysis is important to discover credible findings in nursing due to the fact that nurses provide documentation already and when this is used for research it can improve the effectiveness of care, improve patient satisfaction and health outcomes, as well as reduce healthcare costs. The most important part of Nursing is patient safety and quality of care, research can also allow a reduction is medical errors and deaths.

Clinical significance as Houser (2018) mentioned is reflected to an extent in which an intervention can make a difference in patient’s lives. Clinicians are more interested with this significance rather than results by chance.

Houser (2018) mentioned that statistical significance is when the p value is small which indicates that the probability of the results were due to small chance of being small. If the p value is large then the probability that the results were due to error is large as well. Statistical significance is one of the important measures which determines if the research conducted is useful as evidence and does not eliminate the need for careful thought about the findings for clinical practice.

In this case, clinical significance would be more meaningful to me as it is represented by the effect size, which can indicate how much of an effect is expected. This provides more information in this case for the nurse for evidence based practice versus the statistical significance.

References:

DeCaro, S. A. (2003). A student’s guide to the conceptual side of inferential statistics. Retrieved [April 7 2019], from http://psychology.sdecnet.com/stathelp.htm (Links to an external site.)Links to an external site.

Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Burlington, MA: Jones & Bartlett Learning.