Why do researchers explore and examine data prior to formal analysis?
What will be an ideal response?
Researchers often spend a considerable amount of time exploring the data before launching a formal analysis in order to make sure all data elements are included in one data file, of sufficient quality (such as no coding errors or excessive missing values), and to prepare it for hypothesis testing and model building. If a research project uses several data sources, the separate data files have to be combined and merged. Inspecting the distribution of values is important for evaluating the appropriateness of the statistical techniques to be used for hypothesis testing or model building. Since normal distribution is important to statistical inference, a normal probability plot may be used to pair each observed value with its expected value based on a normal distribution. If the sample is drawn from a normal distribution, the points will fall more or less on a straight line, and a simple linear regression model may be needed. If the distribution does not appear to be normally distributed, data transformation might be necessary, or some nonparametric techniques can be used. If the plot resembles a mathematical function, that function may be employed to fit the data.
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