Statistical tests methods in nursing are paramount in analyzing the data collected from the people. The importance of having good statistical methods is to ensure the near accuracy results. The results gotten are useful in the preparation of the reports that guides the relevant bodies in ensuring the nursing services are of high quality ((Main & Ogaz, 2016). It, therefore, calls for a high degree of statistical background, which would enable the medical practitioners to plan their activities.
The type of statistics applied is inferential statistics. This is the type of statistics, which purely relies on probability. The calculation done is not actual values and gives an estimate of the desired results (Giuliano & Polanowicz, 2015). This statistical method is controlled by variables that are a result of using a small sample to represent a large data. The data is collected from varied positions and the parameters gotten are an estimate (Main & Ogaz, 2016). It does not portray the real situation but the values are near accuracy.
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Some of the inferential tests used are chi-square, t-test, and analysis of variance. These are very important tests methods, which have been used in most of the research work. They are used to measure the variation of the data and give the correlation of the same (Zellner, Boerst & Tabb, 2007). Use of analysis variance has been used to give graphical correlation and regression of the data. They are used in situations where the data under investigation require curious investigation and proofing the data ( Polit et al, 2017) . The test methods have been used largely by most of the researchers who are doing serious research. The methods are highly valued due to their validity methods.
The level of measurement required for using inferential statistics is the interval data levels of measurement because it provides the most detailed information. Interval data levels of measurement are also appropriate for statistical measures for example, mean of the sample and standard deviation of the sample carried out. Interval level is the most appropriate for inferential statistics because it involves statistical measures.
Inferential statistics use observations, data and some research on a certain sample in order to come up with conclusions about the population in a place (Giuliano & Polanowicz, 2015). For example, inferential statistics can be used to identify factors, which affect all population of orthopedic patients, which is based on the study of the patients. Inferential statistics can be applied in two areas in the nursing research process that is, in estimating parameters where a statistic is taken from your sample data, for example, the mean of the sample and can be used to talk about the mean of the population (Zellner, Boerst & Tabb, 2007). Another area where inferential statistics can be used is in the hypothesis tests where one can use sample data to tackle research questions. For example, a nurse may be interested in knowing the effectiveness of a new cancer drug or even whether taking breakfast among children help better their performance in school (Main & Ogaz, 2016) . Assuming one has sample data on an effective new cancer drug, inferential statistics can be applied in the description of the sample in terms of the sample mean, the standard deviation of the sample and in making a bar chart.
Conclusively, statistical methods are very important in evaluating the data that is important in the nursing recording. The measures employed in statistical tests cut across in all disciplines. You find that every profession must embrace the statically calculation which allows estimation of the results desired.
References
Giuliano K. Karen & Polanowicz Michelle, (2015). Interpretation and Use of Statistics in Nursing Research . ResearchGate.
Main E. Maria & Ogaz L. Veletta, (2016). Common Statistical Tests and Interpretation in Nursing Research. International Journal of Faith Community Nursing
Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Philadelphia, PA: Wolters Kluwer.
Zellner Kathleen, Boerst J., Connie & Tabb Wil, (2007). Statistics Used in Current Nursing Research. Journal of Nursing Education Vol. 46, No. 2
