Hypothetical outcome plots is an effective visualization method to communicate data uncertainty. This repo included several notebooks to demonstrate how this approach is applied under different analysis settings. All notebooks provide step-by-step guides of generating Hypothetical outcome plots in Python:
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Regression_Animation.ipynd: where hypothetical outcome plots help the audience to see alternative trend curves supported by the noisy training data;
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Cannon_shooting.ipynb: where hypothetical outcome plots help the audience to sense the variation in shooting range induced by uncertain shooting conditions;
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Battery_Remaining_Useful_Life_Prediction.ipynb: where hypothetical outcome plots help the audience to understand the battery failure risks with different cycle numbers.
You can find the companion blog here:
Uncertainty Visualization Made Easy With Hypothetical Outcome Plots