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The jackknife, leave-one-out for bias and variance

You have nn observations and a statistic θ^\hat{\theta}, and want its bias and standard error without a formula.

Explain the jackknife: the algorithm, what it estimates, its relationship to the bootstrap, and a case where it fails.

Show a hint

Recompute the statistic nn times, each time leaving out one observation. How much each leave-one-out value moves tells you about variability.

Your answer

This one is open-ended. Work it through, then check your reasoning against the full solution.

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