Statistical Pitfalls: Problems with the Statistical Representation of Fieldwork Data from Social Research

Students, as well as professional research proposals have been rejected by the proposal committee and some grants awarding bodies for lack of statistical representation. Statistics is the science that is dealing with the collection and organisation, analysis and interpretation of numerical data from which conclusions about the variables under study, are made. This contribution to the pathway to ensuring students’ success argues that it would be misleading and inappropriate to suggest that only studies, which are backed-up with statistical tools, are rigorous and meaningful. Previous research has argued that statistical techniques play crucial role for uncovering hidden knowledge. However, in the present paper, the researchers argue that to assign such potency to statistical tools appear misleading especially to students and newer researchers. The paper notes that of about twenty-three statistical tools available for use by researchers, none possesses any investigative quality. What statistics possesses is an analytic strength, whereby numerical and calculative meanings are assigned to assembled data that cannot uncover beyond the strength of the data-collecting instrument. In this paper, the researchers examine the meaning of statistics, the use of language as a tool of statistics, statistical data and its types; scale of measurement and appropriate statistics, and some of the pitfalls in the use of statistical tools in analysing data from social and behavioural studies. The implication of this for students’ research and success are equally highlighted. DOI: 10.5901/mjss.2014.v5n20p144