interpretation in order to arrive at the meaning. For example, in quantitative research, data analysis consists of measurements in numerical values from which descriptions such as mean, mode, range andstandard deviations are made. These data can be put into some order and further divided into two groups: discrete data or continuous data. Discrete data are countable data, e.g. the number of notable items produced during a day’s production. Continuous data are parameters (variables) that are measured and are expressed on a continuous scale, e.g. the height of a person. The analysis of quantitative data varies from simple to more elaborate analysis techniques. The analysis varies with the objectives of the experiment, its complexity and the extent to which conclusion can be easily reached. Data analysis in quantitative research depends on the type of study such as: Correlation study, Prediction study, Causal-comparative research etc. The research analyst breaks down data into constituent parts to obtain answers to research questions (problem statements) and to test research hypotheses. It is only after the interpretation of analyzed data that answers to problem questions are arrived at. Therefore we have to analyze the data first and then explain the result. That is, interpret the results of the analysis done. All we are saying is that, we have to categorize the data, order the data, manipulate the data and summarize the data to obtain answers to the questions. So, it means that the purpose of analysis is to reduce the data to intelligible and interpretable form so that the relations of research problems can be studied and tested. To do all this we need to make use of statistics since the primary purpose of statistics in research is to manipulate and summarize the numerical data and the results obtained, compared with chance expectations. That is, the researcher must have hypothesized that styles of leadership affect group participation in certain ways. The researcher plans an experiment, executes the plan, and gathers data from the subjects. If the research question is: “How do styles of leadership affect group-member participation?” the researcher must put down analysis paradigms or models even when working on the problem and hypotheses. The interpretation takes the results of analysis, makes inferences pertinent to research relations studied, and draws conclusions about the relations, searching for their meaning and implications, (Kerlinger, 2004). There are many kinds of statistical analysis and presentations available and we cannot discuss them all in details here. 3.2 Procedures in Data Analysis MadhuBala, of Indira Gandhi National Open University,( 2005) discussed the following process for data analysis. “Once you have selected the topic of the research and have gone through the process of literature survey, established your own focus of research, selected the research paradigm and methodology, prepared your own research plan and have collected the data; the next step is analysis of the data collected, before finally writing the research report.
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