The relationship between legal standards of proof and thresholds of statistical significance is a well-known and studied phenomena in the academic literature. Moreover, the distinction between the two has been recognized in law. For example, in Matrix v. Siracusano, the Court unanimously rejected the petitioner's argument that the issue of materiality in a securities class action can be defined by the presence or absence of a statistically significant effect. However, in other contexts, thresholds based on fixed significance levels imported from academic settings continue to be used as a legal standard of proof. Our positive analysis demonstrates how a choice of either a statistical significance threshold or a legal standard of proof represent alternative and often inconsistent attempts to balance error costs, and that thresholds based on fixed significance levels generally are not consistent with existing or optimal legal standards of proof. We also show how the statistical testing and legal standards of proof can be reconciled by replacing fixed significance level hypothesis testing with likelihood ratio tests.
The relationship between legal standards of proof and thresholds of statistical significance is a well-known and studied phenomena in the academic literature. Moreover, the distinction between the two has been recognized in law. For example, in Matrix v. Siracusano, the Court unanimously rejected the petitioner's argument that the issue of materiality in a securities class action can be defined by the presence or absence of a statistically significant effect. However, in other contexts, thresholds based on fixed significance levels imported from academic settings continue to be used as a legal standard of proof. Our positive analysis demonstrates how a choice of either a statistical significance threshold or a legal standard of proof represent alternative and often inconsistent attempts to balance error costs, and that thresholds based on fixed significance levels generally are not consistent with existing or optimal legal standards of proof. We also show how the statistical testing and legal standards of proof can be reconciled by replacing fixed significance level hypothesis testing with likelihood ratio tests.
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