The key concept in the chapter is about inferential statistics. The chapter explains that inferential statistics utilizes the idea of probability to establish the methods through which a conclusion on a given population can be obtained. The chapter identifies one of these methods as sampling distribution. The sampling distribution is described in the chapter as an imperative concept utilized in estimating population parameters.
Another concept discussed in the chapter is about the estimation of parameters. This includes several methods discussed under it that are relevant when estimating parameters. These include confidence interval around the mean and confidence interval around proportions and risk indexes. As the chapter explains, confidence interval measures the margin of error when estimating parameters such as the mean, mean difference between groups or proportion.
The last concept explained in the chapter is that of the hypothesis testing. The chapter shows that the aim of this concept is to provide the objective for making decisions as to whether hypothesis supports the data (Polit, 2010). It includes several aspects like null and alternative hypothesis, type I and II errors, levels of significance and critical regions. The last items on hypothesis testing are results of the statistical decision. The level of significance helps control the risks of type I error by limiting the results of the analysis within a given significance level (Stommel& Dontje, 2014). Critical regions determine decision as to whether null hypothesis should be rejected especially when it falls outside the limits of critical decision (Heavey, 2014).
Importance of the Methods to Nursing ResearchUnderstanding statistical methods such as sampling distribution and parameter estimates help nurses to easily develop a quick understanding about a given population under study by choosing a representative sample and examine the characters of the population (Polit, 2010). Subsequently, estimating methods are critical during a research about certain diseases and population as they help estimate whether the information being studied lies within acceptable limits (Park et al., 2014).
The chapter looks at three major concepts under inferential statistics. These are sampling distribution, hypothesis-testing, and confidence interval. The sampling distribution is the main concept, and the remaining two are the key statistical tests majorly used in helping understand the characteristics of data under study. The statistical methods explained in the chapter are important to nursing research as they enhance easy understanding of information. It is, therefore, important for nurses to have these basic concepts when conducting research.
Heavey, E. (2014). Statistics for nursing: A practical approach. Jones & Bartlett Publishers.
Park, L. G., Howie-Esquivel, J., Chung, M., & Dracup, K. (2014). A text messaging intervention to promote medication adherence for patients with coronary heart disease: A randomized controlled trial. Patient Education and Counseling, 94, 261268.
Polit, D. F. (2010). Statistics and data analysis for nursing research (2nd ed.). Upper Saddle River, NJ: Pearson.
Stommel, M., & Dontje, K. J. (2014). Statistics for advanced practice nurses and health professionals. Springer Publishing Company.
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