Data Analysis

1 story
Within Explainers, Timelines & Data, Data Analysis focuses on missing-value policy; outlier treatment and confidence interval determine how the subject works in practice. Differences in correlation caveat, reproducible notebook and chart annotation explain why the same label can produce markedly different results between games.
Writers use confirmed sources and reproducible observation to establish sampling frame, revision control and normalisation method. The practical value becomes clearer when source conflict is considered beside terminology hierarchy. Data Analysis remains the main subject only when that question outweighs the neighbouring topics grouped under Explainers, Timelines & Data.