Which of the following is NOT a key component of exploratory data analysis?

The correct answer identifies statistical testing for hypotheses as not being a key component of exploratory data analysis (EDA). EDA focuses primarily on understanding the patterns, trends, and structures within data before formal statistical modeling is applied. This involves methods such as visualization of data, which allows researchers to see relationships and distributions; descriptive statistics, which summarize key aspects of the data; and data cleaning and preparation, which ensure that the dataset is suitable for analysis.

Statistical testing, on the other hand, is more aligned with confirmatory data analysis, where specific hypotheses are tested against the data to seek statistical evidence. EDA precedes this process, aiming to explore the data intuitively rather than rigidly testing preconceived notions or hypotheses. Hence, while statistical testing is important in the overall data analysis process, it does not fit into the exploratory phase that EDA represents.