You know that the definition of the variance is Var[X] = 1 n − 1 Z...

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You know that the definition of the variance is Var[X] = 1 n − 1Z ∞ −∞ (Xi − µ) 2 dFX(x), so if we have a plug-in estimator S 2 = 1n − 1 Xn i=1 (xi − X¯) 2 and we are interested in SES2 = p Var[S2]we can use the bootstrap to obtain it. Write a function in R calledbootVarSE that computes a bootstrap estimate of the standard errorof the sample variance estimator. Test your function using 100standard random normal draws (that is, rnorm(100)) as datainput.

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Boostrap for the Normal distribution And    See Answer
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