Simulation Problem: In statistical inference, one wishes to estimate unknown population

parameters (for example, the population mean) using observed sample data. A condence

interval is a random interval calculated from the sample data that contains with a specied

probability. The interval has an associated condence level C which gives the probability that

any valid condence interval will contain the true value of the unknown parameter . For

example, assume that the condence level is 95%. Then, if we construct 100 dierent 95%

condence intervals for using 100 independent sets of data, then we would expect about 95 of

them to contain .

a) Use random.expovariate() from Python's random library to create n = 5000 samples of

an exponential distribution with mean 3. Note that in a real-world scenario, the true

distribution of the sample data is not known.

b) Compute the sample mean x of the data.

5. Simulation Problem: In statistical inference, one wishes to estimate unknown population parameters 0 (for example, the population mean) using observed sample data. A confidence interval is a random interval calculated from the sample data that contains 0 with a specified probability. The interval has an associated confidence level C which gives the probability that any valid confidence interval will contain the true value of the unknown parameter 0. For example, assume that the confidence level is 95%. Then, if we construct 100 different 95% confidence intervals for 0 using 100 independent sets of data, then we would expect about 95 of them to contain 0.a) Use mndomempovariate (A) from Python\"s random library to create n = 5000 samples of an exponential distribution with mean 3. Note that in a realworld scenario, the true distribution of the sample data is not known. b) Compute the sample mean it of the data