Importance of Research Data

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Importance of good quality data and DATA ANALYSIS for Research Methods INTRODUCTION Conducting a survey is often a useful way of finding something out, especially when `human factors ' are under investigation. Although surveys often investigate subjective issues, a well-designed survey should produce quantitative, rather than qualitative, results. That is, the results should be expressed numerically, and be capable of rigorous analysis. The data obtained from a study may or may not be in numerical or quantitative form, that is, in the form of numbers. If they are not in numerical form, then we can still carry out qualitative analyses based on the experiences of the individual participants. If they are in numerical…show more content…
The task here is to create a diagram of the topic that includes clearly defined variables (independent, dependent, etc.) along with the relationships of those variables and key factors that influence the variables and the relationships. This task is often done in conjunction with the development of the research questions and it is an iterative process. [pic] THE IMPORTANCE OF GOOD QUALITY DATA Scientific research is used by academics in a wide scope of academic disciplines such as social sciences, public health, biostatistics, education, social work, public administration, and business administration; and by practitioners engaged in marketing, commerce, and industry. Data are the basis for all scientific research. Collecting good quality data plays a vital role in supplying objective information for the problems under study so that some analytical understanding of the problems and hence solutions can be obtained. Making decision on the basis of poor quality data is risky and may lead to disastrous results, as the situation may be distorted and hence all subsequent analyses and decision making will rest on a shaky ground. WHAT IS THE IMPORTANCE OF DATA ANALYSIS ? Data analysis is important to businesses will be an understatement. In fact, no business can survive without analyzing available data. Visualize the following situations: [pic] A pharma company is performing trials on number of patients to test
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