RESPONSE TO MY CLASSMATE ANNOTATED BIBLIOGRAPHY

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I have to respond to .a classmate at annotated bibliography with the following; Address the content of each colleague’s analysis and evaluation of the topic and of the integration of the relevant resources. Extend or constructively challenge your colleagues’ work. Student annotated bibliography below : Data Assumptions and Nonparametric Analyses             Nonparametric procedures analyze data for an independent samples t-test (Green & Salkind, 2017). When the independent samples t-test meets the assumptions, a parametric test is a more robust analysis; however, when the independent samples t-test does not meet the assumptions, the nonparametric analysis may be a preferred analysis (Green & Salkind, 2017). The basis of a parametric test is on the assumption about the distribution of the underlying population from the taken sample; the normal distribution of data is the most common parametric assumption (Hoskin, 2012). On the other hand, nonparametric tests have no reliability on assumptions about the shape of the underlying population distribution parameters (Hoskin, 2012).              Hoskin (2012) provided an example of a parametric test and its nonparametric statistical test equivalent. Hoskin (2012) mentioned that the type of analysis was to compare means between two distinct or independent groups. The example looked at whether the mean systolic blood pressure (at baseline) for patients assigned to placebo differed from the mean for patients assigned to the treatment groups (Hoskin, 2012). Hoskin (2012) outlined that the parametric procedure was the two-sample t-test and the nonparametric procedure was the Wilcoxon rank-sum test.              Salahuddin et al. (2015) discussed using a nonparametric test to determine whether there was an association between job satisfaction and other demographic and work-related factors; they used the chi-square test. When the independent samples t-test does not meet the assumptions, the nonparametric analysis may be preferred (Green & Salkind, 2017).   References Green, S. B., & Salkind, N. J. (2017). Using SPSS for Windows and Macintosh: Analyzing and  understanding data (8th ed.). Pearson.  Hoskin, T. (2012). Parametric and nonparametric: Demystifying the terms. In Mayo Clinic (Vol.  5, pp. 1-5). Salahuddin, A. F., Khan, M. M. A., Ullah, M. O., & Jahan, N. (2015). Job satisfaction and  university administrative staffs: An exploratory study. Journal of Applied Quantitative  Methods, 10(4), 27-39.