Which statistical technique is commonly used by data analysts?

Regression analysis is a statistical technique that examines the relationship between a dependent variable and one or more independent variables. It is widely used by data analysts to make predictions, understand relationships, and assess the strength of correlations in data. By fitting a regression model to a dataset, analysts can derive insights about how changes in the independent variables impact the dependent variable. This allows for data-driven decision-making and forecasting, making regression analysis a foundational tool in the field of data analysis.

Other techniques, such as image recognition and network analysis, serve different purposes. Image recognition typically involves machine learning methods to identify patterns in visual data, which is not a primary statistical technique. Data encryption, on the other hand, relates to securing information and does not involve statistical analysis at all. Therefore, regression analysis stands out as the correct choice because it directly pertains to the statistical methods commonly employed by data analysts.