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What is Data Dredging?

 , November 05, 2015 updated on October 05, 2017
Data dredging is the automated statistical analysis of large sets of data.
It is similar to data mining with the key difference being that data mining starts with a hypothesis, or something that you expect to find in the data. Data dredging is an automated search for statistical patterns that doesn't start with a hypothesis.
Data dredging tests large sets of data against known statistical models to generate matches. As such, it runs a risk of finding coincidental patterns in data that have no real meaning. In other words, it is a process of finding a pattern that fits the data rather than confirming a pattern with data. As such, data dredging is associated with ethical issues because it's an easy way to create a research paper that looks valid but is essentially auto generated. Nevertheless, the technique does have potential to discover patterns in data that have meaning.
Overview: Data Dredging
FunctionStatistical Analysis
DefinitionAn automated search for statistical patterns in data.
ValuePattern discovery as a starting point of analysis.
RiskData Dredging tends to produce patterns that exist by chance that have no meaning. In other words, results may lack significance.
Related TechniquesStatistical Model
Business Analysis

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