What type of analysis employs descriptive statistics and data visualization?

The correct answer is exploratory analysis. This type of analysis focuses on summarizing and visualizing data to discover patterns, trends, and relationships within the dataset. Descriptive statistics, such as measures of central tendency (mean, median, mode) and variability (range, variance, standard deviation), are employed to provide a comprehensive overview of the dataset.

In addition to these statistics, exploratory analysis heavily relies on data visualization techniques like histograms, scatter plots, and box plots, which help in illustrating the data in a more interpretable manner. This approach is crucial in gaining initial insights before moving on to more complex analyses or modeling techniques.

Extraction typically refers to the process of obtaining data from various sources but does not inherently analyze or visualize that data. Deep learning involves machine learning techniques that model complex relationships and is not primarily concerned with descriptive statistics or initial data insights. Classification is a type of supervised learning technique used to predict categorical outcomes based on input features, and it requires specific algorithms rather than exploratory techniques to derive insights.