Reply to peer 1
Regarding the T-test result obtained from the experiment, the statistical test assumes that the results from the trial are continuous because it references from the normal distribution of the students. The analysis of the p-value, which is relatively low at 0.22 gives us the likely probability of the result when observing the outcome from the null hypothesis perspective. More so, the small p-value obtained lowers the support that we would put in favor of the null hypothesis (Silvia, & Marina, 2018). However, statistically, it can never be ruled out that the null hypothesis is wrong because the result obtained from the test is rare since the test can choose a statistically significant value which is less than 0.05 (Krzywinski, & Altman, 2017). I acknowledge that the practical significance of the test depends entirely on the subject matter. Therefore, it will be common to observe the results as statistically significant but not practically significant.
References
Krzywinski, M, & Altman, N. (2017). Interpreting P values. A natureresearch journal . 14, 213-214 doi https://doi.org/10.1038/nmeth.4210
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Silvia, P. & Marina, S.(2018). Determining Significance in the New Era for P Values. Journal of Pediatric Gastroenterology and Nutrition . 67(5), 547-548. doi 10.1097/MPG.0000000000002120
Reply to peer 2
According to my understanding, the paired sample test is essential while comparing the mean obtained from the two-sample tests. However, the student group is independent and therefore, we test whether there is a statistical difference between the mean obtained from the first and the second test (Gelman, and Loken, 2014). Measuring the participants on two occasion but with the same dependent variable, the mean of the outcome is 0.22, which is relatively low compared with the cutoff value of 5%. Hence, minimal chances of obtaining the results which would confirm that the null hypothesis is correct (Ronald, Wasserstein & Nicole, 2016). Further analysis depicts that the average value of the test is 0.48, which is close to the confidence level of 0.05. In this regard, it is essential to disregard the null hypothesis and accept the alternative explanation. Hence, there is a statistical difference obtained by the students before and after taking the test.
References
Gelman, A., and Loken, E. (2014), “The Statistical Crisis in Science [online],” American Scientist, 102. Available at http://www.americansc ientist.org/issues/feature/2014/6/the-statistical-crisis-in-science
Ronald L. Wasserstein & Nicole, A. (2016) The ASA's Statement on p-Values: Context, Process, and Purpose, The American Statistician, 70:2, 129-133, DOI: 10.1080/00031305.2016.1154108
