Understanding Research techniques in nursing - Essay Example

Descriptive statistics Introduction SECTION ONE This section draws its basis from the articles listed as follows, ly: Britt, S.,& E, R. (2009). Research education for clinical nurses: a pilot study to determine research self-efficacy in critical care nurses. Journal Of Continuing Education In Nursing, 10(40), 454-461.Fisher, J., & Marshall, A. (2009). Understanding descriptive statistics. Australian critical care, 22(n/a), 93-977.1. Highlight the descriptive statistics discussed in the article?2. In what way can a nurse employ descriptive statistics to support a course of action?3. In what way is descriptive statistics persuasive?

Descriptive statistics entails the numerical and graphical methods which can be employed with the aim of arranging and sorting data in a bid to ease the analysis process. On that note, the type of descriptive statistical method to be used to describe a particular variable is dependent on the level of measurement employed by the analyst. For instance, there exist two main levels of measurements and they are the nominal and the ordinal levels of measurement (Britt, 2009). In addition to that, the nominal level of measurement entails the grouping of cases into categories.

On the same note, in this level of measurement, the measure of dispersion draws its basis on the frequency of the distribution which is the particular frequency of cases in each category (Fisher& Marshall, 2009). On the contrary, the other level of measurement in descriptive statistics is the ordinal level. Apparently, this level of measurement entails grouping of cases into several groups like the previous case. However, here unlike the first case, the categories have numerical hierarchies where data in this level of measurement are classified in a hierarchical manner; in other words, starting from the lowest to the highest point for instance marks (Fethney, 2010).

Notably, the measures of the dispersion are similar to the nominal level of measurement but they only vary on the arrangement of the data in the groups. Evidently, the role of descriptive statistics is inevitable in the field of nursing; self-efficacy, which is the ability of a nurse to translate research into meaningful evidence in the field of healthcare (Britt, 2009). On that note, through the study of descriptive statistics, a nurse can be able to think critically and reasonably and thus better job performance (Fisher& Marshall, 2009).

It is worth noting that, this particular area of study aids in the building of the thinking capacity of an individual and thus the self-efficacy. Apparently, descriptive statistics can be said to at times very persuasive since it is not a very difficult discipline to venture in as compared to other fields for instance science which may require very complex scientific experiments in order to yield a particular result (Fethney, 2010).SECTION 2This section majorly borrows from it ideas from the following articles, they are:Fethney, J. (2010). Statistical and clinical significance.

Australian Critical care, 10(40), 93-97.Fisher, J., & Marshall, A. (2009).understanding descriptive statistics. Austarlian critical care, 22(n/a), 93-97.1. Why is confidence interval essential in finding the clinical significance?2. Highlight briefly one of the controversies of statistical and clinical significance? Although descriptive statistics plays a huge clinical significance, so does the confidence intervals. On the same point, a scholar, Jacobsen, championed the idea of clinical significance over the statistical one (Britt, 2009).

Furthermore, he went ahead to postulate that the clinical significance was a practical way of determining the value of treatment. Apparently, through the evaluation of the minimum importance difference among a population regarding a particular subject, one can be able to draw appropriate conclusions and therefore, come up with recommendations pertaining to the particular area of interest (Fisher& Marshall, 2009). On the other hand, it is worth noting that, it is argued that the result cannot be significant clinically if they appropriate channels were not followed or the results were by luck.

Therefore, statistical significance is a mandatory condition for the occurrence of clinical significance (Fethney, 2010). However, it has also been argued that clinical significance does not entirely depend on the statistical significance. In summation, a conclusion can be drawn that, a description of clinical significance should be clearly stated for any result measure used (Britt, 2009). In conclusion, it evident that confidence interval and descriptive statistics play a huge role in nursing and consequently in the field of medicine as whole.

To this end, it is essential to analyze this area to appreciate their contribution to our health care.ReferencesBritt, S., & E, R. (2009). Research education for clinical nurses: a pilot study to determine research self-efficacy in critical care nurses. Journal Of Continuing Education In Nursing, 10(40), 454-461. Fethney, J. (2010). statistical and clinical significance. Australian Critical care, 10(40), 93-97. Fisher, J., & Marshall, A. (2009). understanding descriptive statistics.

Austarlian critical care, 22(n/a), 93-97.