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Discuss the Difference between an Exploratory Analysis and a Confirmatory Analysis

Data analysis is a crucial step in research studies as it helps a researcher find meaning in the raw data collected. Exploratory analysis is usually the initial step of data analysis that involves manipulating, questioning and visualizing the raw data to number out what make of the data (Bandalos, 2018). On the other hand, confirmatory analysis involves assessing and evaluating evidence to challenge the assumptions made. Confirmatory data analysis can be perceived as a backward approach whereby one examines the credibility or weighs the pieces of evidence of a result found. Thus, while exploratory data analysis involves manipulating data to derive predictions or conclusions, confirmatory data involves examining and evaluating assumptions or conclusions made.

The exploratory analysis involves looking for clues, trends, patterns, assumptions, missing data as well as unexpected results that may arise from data. Meanwhile, confirmatory data analysis involves processes such as generating estimates, testing hypotheses, valuable analysis, and regression analysis (Bandalos, 2018). Further, confirmatory analysis involves application of statistical tools like inference and significance to assess the evidence.

 The output of exploratory data analysis usually allows the data analysts to proceed to the next steps as they help them decide on what questions or areas to explore. On the other hand, confirmatory analysis helps a data analysist put the findings and arguments into a trial and test its credibility. Bandalos (2018) confirms that explanatory and confirmatory analysis are executed one after the other, but rather they are constantly intertwined to assist a data analyst to derive the most appropriate model for analysis.