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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).
Investigators 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).
The 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,
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