Question

Consider the data thought to follow a Gaussian distribution:

33.1068240, -6.3331469, 22.2903011, -6.9142991, -21.7899524, -12.1741625, 29.2973275, -34.2364631, -4.4113930, -25.7845033, -12.0375226, 17.9397860, -6.2030667, 0.3504070, -19.4854146, -10.5979710, -27.1274107, 20.4247578, 17.0975034, -6.8416016, 0.8700698, -9.9103781, 8.3101956, -6.9263659, -23.7861226, -1.8070511, 8.9497832, 27.5315404, 5.9680535, -2.4057959, 30.4888656, 8.3810280, -12.4548588, -19.5759143

a. Compute the maximum likelihood estimates for the mean and standard deviation.

μ_MLE:

σ_MLE:

b. Compute bootstrap estimates of the mean and sd with 2000 sampling iterations.

μ_BS

σ_BS

c. What are the relative percent differences between the the maximum likelihood estimates and the BS estimates?

|MLE - BS|/MLE * 100%: for μ:

|MLE - BS|/MLE * 100%: for σ:

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My answers were way off!

Seems easy when computing through R but confused.

Answer 1