Inferential statistics enable researchers to apply the data they gather and the conclusions they draw from a particular sample to a larger population. As the name implies, inferential statistics focus on inferring whether there is a relationship between two or more variables. These statistical analyses include t tests and analysis of variance (ANOVA). t Tests are part of a group of statistical tests that test hypotheses; in fact, it is necessary to formulate a hypothesis in order to use a t test, because the results of the test can only be interpreted in the context of a scientific hypothesis.
Inferential statistics such as t tests work well for comparing two groups. Although mathematically equivalent to the t test, ANOVA allows for the comparison of more than two groups. Therefore, when three or more groups are involved, the ANOVA should be used.
In this week’s Discussion, you are asked to locate a current research article that utilizes either a t
test or ANOVA analysis. You provide a summary of the research study and of the study’s application to evidence-based practice. You also examine the article’s use of a t test or ANOVA and how either of those statistical analysis tools helped to inform the article’s conclusions and recommendations.
By tomorrow Wednesday 09/27/17, 8 pm, write a minimum of 550 words essay in APA format with a minimum of 3 references from the list in the instructions area. Include the level one headings as numbered below:
Post a cohesive response that addresses the following:
1) Identify the topic you selected in the first line of your posting. (you can choose any nursing topic from or any other nursing related issue that will be easy to locate a scholarly research article on which uses a )
2) Summarize the study discussed in your selected research article and provide a complete APA citation. Include in your summary the sample, data sources, inferential statistic utilized, and findings.
3) Evaluate the purpose and value of this particular research study to the topic.
4) Did using inferential statistics strengthen or weaken the study’s application to evidence-based practice?
Gray, J.R., Grove, S.K., & Sutherland, S. (2017). Burns, and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (8th ed.). St. Louis, MO: Saunders Elsevier.
This excerpt elaborates on how statistics are used to examine causality using procedures such as contingency tables, chi-squares, t tests, and analysis of variance (ANOVA).
This chapter discusses inferential statistics, sampling error, sampling distributions, and the laws of probability. The chapter also introduces key terms such as standard error of mean, hypothesis testing, and parametric test.
This chapter considers the various forms of the t test, including the two-sample t test, Kolmogrov-Smirnov test, independent groups t test, and dependent groups t test. The chapter also discusses the many variables involved in these tests such as effect size, meta-analysis, and Cohen’s d.
Chapter 7, “Analysis of Variance” (pp. 137–146 and 155–158)
The first part of this chapter introduces the basic assumptions, requirements, general logic, and terminology surrounding analysis of variance (ANOVA). The second excerpt focuses on sampling distribution of the F ratio and the null and alternative hypotheses.
Jadcherla, S. R., Wang, M., Vijayapal, A. S., & Leuthner, S. R. (2010). Impact of prematurity and co-morbidities on feeding milestones in neonates: A retrospective study. Journal of Perinatology, 30(3), 201–208. doi:10.1038/jp.2009.149
This article outlines the procedures and results of a retrospective study of how perinatal and comorbidity factors affect the rate at which infants meet feeding milestones. The article also includes an application of inferential statistics to the results of the study.