Discussion question - Coursework Example

Discussion Question Differences between Parametric and Non-Parametric Tests In parametric tests, a complete knowledge about the participants of a study can be ascertained. These tests are duly considered to be powerful as compared to other tests. In terms of differences, absence of data regarding the participants and their nature is witnessed in non-parametric tests. Therefore, assumptions cannot be made regarding the same. Non-parametric tests are generally ineffective in comparison with parametric tests (Neideen & Brasel, 2007).

Examples of the Tests and Their Appropriates In Terms of UsageAn example of parametric test is ‘Analysis of Variance’ (ANOVA), which is employed to analyze the differences prevailing amid groups over certain variables. Thus, it can be affirmed that this test is appropriate to use while measuring the efficiency of distinct variables that remain present within a study. Similarly, an example of non-parametric test is reckoned to be ‘Kruskal-Wallis Test’, which is applied to evaluate three or beyond samples.

These tests can be used in the presence of a single nominal and measurement variable and are executed upon ranked data (Hecke, 2010).Discussion about the AssumptionsInvestigators ought to make certain basic assumptions to conduct ANOVA. In this regard, the values of errors must be considered as zero with assuming the errors as independent. In this similar context, certain assumptions must also be adhered by the investigators while running ‘Kruskal-Wallis Test’. An ordinal scale must be used to assess the two variables.

The independent variables must inculcate in excess of two independent groups (Hecke, 2010). Data Analysis PlanThe data analysis plan involves a number of steps. These include identifying the research problems, specifying assumptions and drawing references. Specially mentioning, to address the study hypothesis, one can make greater use of ‘multiple t-tests’. By considering the fact that the study hypothesis is based on nursing criteria, one of the measures relating to central tendency i.e.

‘mode’ will be reported for demographic variables. This will aid in measuring all the frequencies of the collected values, making the study hypothesis quite reliable and justified (METU, n.d.).ReferencesHecke, T. V. (2010). Power study of Anova versus Kruskal-Wallis test. Articles, 1-6.METU. (n.d.). Central tendency: Mean, media, mode. Retrieved from http://ocw.metu.edu.tr/pluginfile.php/2410/mod_resource/content/0/lectures/3-central%20tendency-NC.pdfNeideen, T., & Brasel, K. (2007). Understanding statistical tests.

Journal of Surgical Education, 64(2), 93-96.