A research scholar might have in-depth knowledge of his own field, but his knowledge of statistics can be just elementary. For a dissertation writer, this can be a setback. We can easily assume that the significance of the statistical work in the dissertation will be directly proportionate to its level of complexity.
The research methodology and statistical analysis chapters are the two pillars which strongly support the research document. Completing these chapters involves a series of steps. The process starts with forming the hypothesis. This task is as essential as laying the foundation of the research work. By stating the hypothesis, we try to deduce a relationship between a set of variables. It is based upon facts and, if proved, would become a part of the theoretic body related that subject. At the commencement of the research, we assume from certain conditions that such a theory can exist. The dissertation is the document that will prove whether the relation assumed is real or not. This is done by constructing a model with the data that we have collected and applying various tests on it.
For collecting data, first a questionnaire will have to be formed. The questions included should address the issues raised in the research. The researcher can refer to the literature for forming the questionnaire. The data are then collected through primary or secondary sources. It is best to gather the data personally, to facilitate a better understanding of the responses and ask follow up questions, if required.
After the collection, cleaning and arrangement of data, comes the actual analysis. The research methodology to be adopted for analysis should be decided. This can be done with the assistance of an expert statistician. Most of the researches require a multivariate analysis, which has the following parts: Examining the data, factor analysis, multiple regression analysis, multiple discriminant analysis, conjoint analysis, cluster analysis, logistic regression and structured equation modelling. Depending upon the analysis that one is undertaking, the modules and tools need to be selected. There are several tools like AMOS, SPSS, Stata, E-views, SAS and R, which are popularly used for statistical analysis.
A precise analysis and clear inference are a must for reaching the desired conclusion. Hence, this chapter should be done with the greatest caution.
