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🧪 Technology Data Science Simulation

Interactive data-science simulator: generate a noisy 3D dataset, tune the outlier fraction, and watch a Z-score threshold flag and clean anomalies in real time, with live mean, standard deviation and correlation readouts before and after cleaning.

Machine Learning & Neural Networks2DModerate60 FPS📱 Mobile-adapted

Real datasets are never perfectly clean — sensor glitches, entry errors and rare edge cases all show up as points that sit far outside a feature's normal range. This simulator generates a synthetic 3-feature dataset with a tunable share of injected outliers, renders it as a live 3D scatter plot, and applies a standard Z-score threshold to flag every sample whose deviation from the mean exceeds a chosen number of standard deviations on any axis. Adjust the sample size and outlier fraction to regenerate fresh data, drag the threshold to see the accept/reject boundary tighten or loosen in real time, and watch the standard deviation and x–y correlation change as flagged points are removed — a compact, hands-on view of the data-cleaning step that precedes almost every statistical model.

⚙ Under the hood

This simulation introduces the core concepts of data science, demonstrating how data analysis techniques can be applied to solve real-world problems. It covers aspects like data cleaning, visualization, and statistical modeling.

Data Science

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install