T test chart | RSCH 8210 – Quantitative Reasoning and Analysis | Walden University
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The study involves 84 patients who were selected from a physiotherapy department to undergo an eight week training attended thrice per week. Participants were assigned to the MP Group (MPG) (n =29), MP plus Static Back Endurance Exercise Group (MPSBEEG) (n =27) or MP plus Dynamic Endurance Exercise Group (MPDBEEG) (n =28) using permuted randomization (Mbada C. et al, 2014).
One way analysis of variance was used to investigate the general characteristics of participants and pain intensity by the given treatment groups.
The author used one-way analysis of variance since the study wanted to examine the relationship on characteristics of patients over different levels or groups making ANOVA suitable and appropriate in testing statistical significant of the difference in means for the pain intensity scores.
One-way analysis of variance is the most suitable test statistic in a place where we have one continues variable whose mean is compared in over two categories or groups. It is therefore suitable in article.
The author displayed tables of analysis but there were no graphs presented in the article. Tables reported the results of the descriptive and test statistics but a graph would have made easy understanding of the results at a glance.
The results showed that mean age, height, weight and BMI of the participants was 51.8 ± 7.35 years, 1.66 ± 0.04m, 76.2±11.2 Kg and 27.2 ± 4.43 kg/m2 respectively. The F-statistics for the groups showed that they were comparable.
The results of the study did not stand alone and were dependent on other tests and external articles in order to make conclusions of the subject.
The author reported the effect size as 0.25. According to Cohen, 0.1 represents a small sample size, 0.3 medium and over 0.5 shows a large sample size. In this case, the sample size is medium and therefore can be meaningful to the study (Rice M. & Harris G., 2005).