Lab 8, Unbiased Estimator(Due Apr. 17, 11:59 PM, 2015)
Shanshan Zhang, tuf14438@temple.edu Illustration of unbiased estimator.
Contents
Question 1: load poiss.mat, download link
http://nymph332088.github.io/CIS2033/2033/Labs/Lab8/poiss.mat . Let the discrete random variable 
be the number of customers visiting ABC Bank in a hour. We know that $X ~ Poiss(lambda). The poiss.mat stores such information: 1000 records. 1.1) Draw the histogram of the 500 data samples. 1.2) Estimate lambda; 1.3) Based on the computed lambda, randomly generate 500 data samples from Poiss(lambda)
Question 2: load norm.mat.
http://nymph332088.github.io/CIS2033/2033/Labs/Lab8/norm.mat Let the continuous random variable be the price changes of the product XYZ. Positve values mean its price is increased and negative values means its price is decreased. We know that X ~ N(mu, sigma^2). The norm.mat stores 1000 records of such information. Please load the data and 2.1) Draw the histogram of the 1000 data samples. 2.2) Estimate mu and sigma; 2.3) Based on the computed mu and sigma, randomly generate 500 data samples from N(mu, sigma^2)
Hint code for question 1:
% Download the data from the website, then load('poiss.mat'); % Esitimation: lambda1 = mean(X); % Random generation: data1 = poissrnd(lambda1,500,1);