Detect and Qualify Outliers with the Right Method
Data & Analyse
Choose a defensible outlier-detection method for your variable and qualify whether each anomaly is an error or a signal.
anomaly-detectiondata-cleaningdata-qualityoutliers
LA@lacauze
0
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4 prompts · #statistics
Choose a defensible outlier-detection method for your variable and qualify whether each anomaly is an error or a signal.
Get an honest, jargon-free reading of your statistical results, separating significance from importance and flagging biases.
Design a sound A/B test, size it properly, then analyze results with the right test and honest caveats about significance.
Build a complete, step-by-step EDA plan tailored to your dataset, columns, and analysis goal before you write a single line.