Chi-squareStatistic

Chi-squarestatistic is a typical tool used when it comes to the analysis ofgroup differences, where dependent variables are investigated at anominal stage. It is a distribution-free tool, and just like othernon-parametric tools statistics, it is vigorous in relation to thedistribution of the data. Explicitly, the tool does not need equalityof variances in the groups under study (McHugh, 2013). The statisticallows the evaluation of not only the dichotomous independentvariables, but also multiple group studies.

Thenotable difference between this statistic and other distribution freestatistic as well as some parametric ones is that the figures used inthe computation of the Chi-square are considerate of the performanceof each party in the study. This detailed approach has provided astable platform for researchers to understand the results found andalso to find out more about the statistic than from others do (Jin etal, 2015).

Chi-squarebeing an important statistic should, therefore, be complemented by astrong statistic. In most cases, the Cramer`s V has been used to testthe data collected from a significant Chi-square (Lesperance et al,2016). Advantages of using this type of statistic range from itsvigorousness in relation to data distribution, its computation iseasier, its detailed feature, its flexibility to its ability to beapplied in various studies. However, it is limited to the sample sizeunder study and in some cases like the one discussed the correlationproduced is low.

References

Jin,C., Ma, T., Hou, R., Tang, M., Tian, Y., Al-Dhelaan, A., &ampAl-Rodhaan, M. (2015). s Feature Selection Basedon Term Frequency and Distribution for Text Categorization. IETEJournal Of Research (Taylor &amp Francis Ltd),61(4),351-362. doi:10.1080/03772063.2015.1021385.

Lesperance,M., Reed, W. J., Stephens, M. A., Tsao, C., &amp Wilton, B. (2016).Assessing Conformance with Benford’s Law: Goodness-Of-Fit Tests andSimultaneous Confidence Intervals. PLoSONE,11(3),1-20. doi:10.1371/journal.pone.0151235.

McHugh,M. L. (2013). The Chi-square test of independence. BiochemiaMedica,23(2),143-149. doi:10.11613/BM.2013.018.