Type I and II Error describe the possible errors we might make when drawing conclusions about the DGP based on our data.
Type I error is when we should adopt the empty model but we adopt the complex model in error.
Type II error is when we should adopt the complex model but we adopt the empty model in error.
Model We Adopt Based on Data | What’s Really True |
Empty Model (𝛽1 = 0) | Complex Model (𝛽1 ≠ 0) |
Empty Model | Correct Conclusion | Type II Error We should adopt the complex model but we adopt the empty model in error |
Complex Model (Reject Empty Model) | Type I Error We should adopt the empty model but we adopt the complex model in error | Correct Conclusion |
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