Question

Question A)
Let us consider a higher variance situation, where σ^2 = 10.0. Imagine you know this variance, and that the data comes from a Gaussian, but that you do not know the true mean.

I ran the code to get 30 samples, and compute one sample average M.
So I got M => Mean is -0.464551593793077 and Standard deviation is 107.58723717466896.

What is the 95% confidence interval around this M? Give actual numbers.

Can you use Chebyshev’s inequality theorem to solve this? if you could please could you write the step solution?

Question B)
Now assume you know less: you do not know the data is Gaussian, though you still know the variance is σ^2 = 10.0. Use the same 30 samples from Q(A)( Mean is -0.464551593793077 and Standard deviation is 107.58723717466896.) and resulting sample average M. Give a 95% confidence interval around M, now without assuming the samples are Gaussian.

Can you use Chebyshev’s inequality theorem to solve this? if you could please could you write the step by step solution?

Thank you in advance

Answer 1