Which approach involves a statistical examination for understanding data sets?

The correct answer is the approach that involves a statistical examination for understanding data sets, which is exploratory data analysis (EDA). EDA is a crucial phase in the data analysis process that focuses on analyzing data sets to summarize their main characteristics, often using visual methods. By employing various statistical techniques, such as descriptive statistics, graphical representations (like histograms, box plots, and scatter plots), and correlation analysis, EDA helps in uncovering patterns, spotting anomalies, and testing hypotheses. This approach allows researchers and analysts to gain insights into the data before applying more formal modeling techniques.

In contrast, data validation involves checking the accuracy and quality of data before analysis to ensure that it meets certain criteria or standards, rather than focusing on understanding the data set’s characteristics. Listwise deletion is a method used in handling missing data during statistical analysis, specifically by excluding entire cases from analysis if any of their data points are missing. Predictive replacement, on the other hand, relates more to filling in missing data with predicted values rather than examining the overall structure and patterns within a data set. Hence, these other approaches serve different purposes and do not emphasize statistical examination aimed at understanding data sets in the same way that exploratory data analysis does.