Quantitative research can be described as the investigation of a social problem using a number based approach. It involves a researcher collecting statistics, first hand or by secondary sources such as from the church, police, school, hospital or state agency. Also researchers can use survey instruments or questionnaires to collect qualitative data by asking participants to compose their own answers. In this instance, most of the questions will be open ended and participants will get the opportunity to provide reasons for their choice or supply additional information in support of their opinion. Students should have expert knowledge of assumptions,knowledge of research design, knowledge of methods of integrating measurement and data analysis, knowledge of levels of measurement and knowledge of data interpretation. Moreover, graduate students should harmonize or blend these five knowledge areas creatively and feasibly in their research.
In quantitative research assumptions refer chiefly to the characteristics of the data. Other assumptions can be drawn from social theory upon which the research is being anchored. Before collecting data the student should be clear about the assumptions of the data to be used for answering the research question. It is important that the student identify whether the data are distributed normally or not. This will assist in test selection provided a hypothesis is being tested. Therefore, he or she may select a parametric test like the multiple correlation to ascertain whether any relationships between variables exist. Alternatively, the t-test or analysis of variance may be employed to measure differences in means between two or among more than two groups or samples selected independently. If the data are not normally distributed equivalent non parametric tests such as chi square tests of association and the Mann Whitney test of difference will be selected. Students should be able to explain the assumptions of each test and demonstrate to readers that these assumptions have been met. Depending on the purpose of the study; the good student should possess knowledge of assumptions such as normality, randomness, equality of variance, linearity and independence.
Theories have a number of assumptions about correlation, causality and effects of behavior. Knowledgeable students should be able to point out the relevance of each of these to their study. The student researcher should make it known whether the data enable the determination of correlation or causality. Consequently theory selection, an essential epistemological feature of quantitative research, will require the student to demonstrate a perfect fit between theory and hypotheses. In other words, the student would know that theoretical assumptions should influence the selection of hypotheses to be tested.
It is expected that graduate students should have advanced knowledge of quantitative research designs and their applications. They should be capable of defining research design as a series of steps or procedures logically ordered for data collection and analysis. The graduate must explain that research design is the methods and materials employed in executing the study and is analogous to a plan when skillfully or appropriately implemented produces excellent outcomes. It must be clear to …