MaleAdolescents with Conduct Disorder
MaleAdolescents with Conduct Disorder
Fromthe previous discussion, the collection method covered severaltechniques that were appropriate for the study. The methods of datacollection would be salient in determining the use of the data andhow they are to be analyzed. For a proper analysis of the data, theorganization would play a major role since a poorly organized datawould be hard to analyze. First, the information will be organizedaccording to the geographical sequence. The factors that affect theadolescence today could be influenced by several other factors thatthe geographical location would play a major role. In this sequence,the data would be salient in understanding the exact effects and thelevel of their consequences. Geographical location would show how theadolescent men from different locations share some characteristics.Secondly, the size of the adolescent men from different places wouldform another basis of data organizations. From the study, the chancesof influences among the adolescents could be different depending ontheir level of influence. Areas with more adolescents could havehigher rate of influence compared to areas of lower population(Collector& Module, 2011).
Forthe level of measurements, rating scale would be the mostappropriate. This would be applied depending on the location ofinterests and the population to be considered. In several cases, theadolescents are not afraid to open up about their behaviors sincethis forms part of their conduct. In this study, the rating scalewould be employed in understanding how the different conducts can bedetermined. In the case of the adolescents, determining the issue ofconduct will be placed at a maximum scale of five or ten where therespondents will base their schemes. The person with the best conductwould score the maximum and the least would score the possibleminimum. In this manner, it would be easier to determine the averagerate of conduct of the adolescents in a specific location and presentthe data in a numerical format. Since this is a psychologicalexperiment, it would be easier in coming up with a better way ofpresenting the psychological data mathematically for easier analysis(Schellings,2011).
Inthe inspection of the organized data, the organization and the natureof the collected data are important. First, correlation will be bestsuited for the psychological data types. In this format, correlatingthe results found in the different forms of findings would give abetter conclusion. In determining the difference and the effects ofboth geographical location and the effects of population, comparisonwould be appropriate. In correlation, the variables would be usedagainst the behaviors as indicated on the scales and properconclusion drawn. Correlation takes into control the effects of thespecific variables against one another based on the chosen variables.Causation will be equally employed in figuring out the causes of theconduct disorder based on the chosen variables (Chinapaw,Mokkink, van Poppel, van Mechelen, & Terwee, 2010)
Inthe computation of data, mathematical analysis is necessary. From theabove discussion, it has been noted that the data will be useful innumerical format and the final computation. The descriptivestatistics that would be graphed would be the population of theadolescents against the conduct measured in the given scale. Thegeographical location would be useful in coming up with thelikelihood of influence and the total population. For this givendata, the measured conduct against the population of the particularlocation would be used in giving the graphical conclusion (Leech& Onwuegbuzie, 2009).
Chinapaw,M. J. M., Mokkink, L. B., van Poppel, M. N. M., van Mechelen, W., &Terwee, C. B. (2010). Physical activity questionnaires for youth: asystematic review of measurement properties. SportsMedicine (Auckland, N.Z.),40(7),539–563
Collector,D., & Module, F. G. (2011). Qualitative Research MethodsOverview. QualitativeResearch Methods A Data Collectors Field Guide,2005(January),1–12.
Leech,N. L., & Onwuegbuzie, A. J. (2009). A typology of mixed methodsresearch designs. Qualityand Quantity,43(2),265–275.
Schellings,G. (2011). Applying learning strategy questionnaires: Problems andpossibilities. Metacognitionand Learning,6(2),91–109.