Inhandling the data, the focus is on the interaction between the twotypes of analysis. The differential comparison of the posttest andpretest scores in each group of treatment is identified. The firststep is to find out whether there is a relationship between theselected groups. An interaction occurs when there is a variance inthe difference between the treatment groups. If the is difference issimilar in each group, then there is no association. The test focuseson the mean difference score concerning the treatment group inrelation to the mean difference score of the control group. The datacollected will thus be summarized, calculating the average andstandard deviation (Huitema,2011).
Thetechnique is the best in handling the data as it gives a crossanalysis on the performance of students. In the context of analysis,the method is applicable due to the nature of data collected. Thedata is continuous with different kind of variables.
Thetechnique is regarded as the best in interpreting the impact of thetraining program using the data taken. One is able to see the extentor magnitude of change from the variables under study. Thequalitative nature of the survey also necessitates the use of thetechnique (Kimand Willson, 2010).
Thedesign helps the researcher in comparing the final results betweengroups giving them an overall idea on the effectiveness of treatmentor the intervention (Rana,Singhal, and Singh, 2013).The researcher can observe how the groups changed between the tests,from pretest to posttest and the improvement over time. If there is asignificant improvement from the control group, then reasons areuncovered to explain the cause. Furthermore, the technique helps incomparing the scores in the two groups and ensures that the processof randomization was effective.
Huitema,B. (2011). The Analysis of Covariance and Alternatives. WileySeries In Probability And Statistics.http://dx.doi.org/10.1002/9781118067475
Kim,E. & Willson, V. (2010). Evaluating Pretest Effects in Pre-PostStudies. EducationalAnd Psychological Measurement, 70(5),744-759. http://dx.doi.org/10.1177/0013164410366687
Rana,R., Singhal, R., & Singh, V. (2013). Analysis of repeatedmeasurement data in the clinical trials.JournalOf Ayurveda And Integrative Medicine, 4(2),77. http://dx.doi.org/10.4103/0975-9476.113872