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Running forecast accuracy backtest analysis...
Sent to — interactive charts, statistical results, R code, and AI insights.
Analyze another fileStandard-library analysis: how good are the forecasts you already made? Map the period, the forecast, and the actual outcome — and optionally the horizon each forecast was made at — and get the full scorecard: MAE and RMSE in your own units, MAPE with its zero and asymmetry traps handled explicitly, sMAPE, MASE against both the naive and the seasonal-naive baseline, bias as a mean error plus the share of periods over- and under-forecast, a Diebold-Mariano test of whether the forecast really beats a baseline rather than just printing two numbers next to each other, actual against forecast over time, the error distribution, and accuracy broken out by calendar period and by forecast horizon.
Interactive line visualization
Interactive table visualization
Interactive bar visualization
Interactive histogram visualization
Interactive bar visualization
Interactive table visualization
Interactive table visualization
Plain-English interpretation — what the numbers mean, what's significant, and what to do next.
Grade a demand or revenue forecasting process against what actually happened
See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.
Run any analysis on your own data — validated R analyses, interactive reports, AI insights, and PDF export.
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