📊 From Raw Numbers to Insight

About this simulation

Every hive inspection produces numbers — weight on a scale, mite drop on a sticky board, brood-nest temperature from a probe. On their own, rows of numbers hide patterns. This lab takes one season of synthetic inspection data from a 12-hive apiary and renders it as three chart families beekeepers and data analysts actually use: a per-hive bar chart, a time-series scatter plot with a trend line, and a statistical-process-control style band that flags outliers automatically.

How it works

• Bar chart mode — one bar per hive shows that week's reading, so you can spot the weak or booming colony at a glance.
• Scatter + trend mode — every hive's weekly reading becomes a point along the season; a trend tube traces the colony average, and a translucent band marks the control limits.
• Outlier threshold — points or bars further than this many standard deviations from the colony mean turn red, exactly how an alerting dashboard flags anomalies.
• Lower the threshold and normal seasonal swings start getting flagged as "problems" — a hands-on lesson in choosing sensible alert bounds.

Controls

• Metric — switch between hive weight, Varroa mite drop and brood temperature.
• Chart type — toggle between the bar-chart and scatter/trend views.
• Week — scrub through the 52-week season; the bars and the time marker follow.
• Outlier threshold — tighten or loosen the anomaly flag in standard deviations (σ).
• ↺ Resample data — generates a fresh synthetic season. Drag to rotate, scroll to zoom.

Did you know?

Statistical process control charts, borrowed from manufacturing quality control, are increasingly used in precision beekeeping: a hive-weight or mite-count reading that drifts outside its normal band is often the first sign of swarming, disease or queen failure — well before it is visible at the entrance.