How to Read Your Results

After running regression, the Results tab shows several key metrics:

  • — how well the model fits (0 to 1; higher is better)
  • Coefficients — how much each variable changes the output per unit increase
  • p-values — whether each variable is statistically significant (p < 0.05 = significant)
  • Residuals — difference between predicted and actual values
  • RMSE — average prediction error in original units
General R² guidance:
  • R² > 0.8 → strong model
  • R² 0.6–0.8 → acceptable for industrial data
  • R² < 0.6 → try transforms or collect more samples
Residuals should look like random noise — any pattern means the model is missing something.
Try it in the app
Try: Run regression → read R² and RMSE in the Stats cards → look at each coefficient's p-value in the Coefficients table. A p-value > 0.05 suggests that variable may not be adding value.
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Run this on your own data

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