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The Sharpe ratio is best utilized for evaluating
Type I Error
The incorrect rejection of a true null hypothesis, or a "false positive," in hypothesis testing, indicating that the test suggests an effect that does not actually exist.
Type II Error
A statistical term referring to the error that occurs when a false null hypothesis is not rejected, indicating a false negative finding.
Type II Error
The error that occurs when a false null hypothesis is not rejected; failing to detect an effect that is present.
Type II Error
A statistical error that occurs when a test fails to reject a false null hypothesis, also known as a false negative.
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