hen it comes to data mining, why may analysts choose EDA over hypothesis testing?
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When it comes to data mining, why may analysts choose EDA over hypothesis testing?
Step by step
Solved in 4 steps
- What is the difference between exploratory data analysis (EDA) and hypothesis testing when it comes to data mining? Why do analysts use EDA?Why do analysts use EDA, and how does it differ from hypothesis testing in the context of data mining?Why do some analysts choose empirical data analysis (EDA) over hypothesis testing when it comes to data mining?
- Understanding the distinction between EDA and hypothesis testing, as well as why analysts may favor EDA while conducting data miningWhat's the difference between EDA and hypothesis testing, and why may analysts favor EDA when data mining?How does EDA vary from hypothesis testing in the context of data mining, and why do analysts utilise it?
- The difference between EDA and hypothesis testing, and why analysts may prefer EDA when doing data miningWhen it comes to data mining, this article illustrates why analysts may find it more beneficial to use EDA rather than hypothesis testing.In addition, the reasons why EDA could be a better choice than hypothesis testing when it comes to data mining.
- When mining data, analysts may prefer to use EDA rather than hypothesis testing for the reasons that are explained here.As well as why EDA may be preferable to hypothesis testing during data mining.The distinction between EDA and hypothesis testing, as well as why analysts may favor EDA during data mining.