확률 및 랜덤변수 hw1

소개

아주대 확률 및 랜덤변수

목차

1. Simulate the experiment of a coin toss with P(head) = p as follows:

2. Plot the following PMF of the binomial random variable X using MATLAB:

3. The De Moivre-Laplace theorem is an approximation of the binomial
distribution to a normal distribution, i.e.,

< 참고문헌 >

본문내용

1. Simulate the experiment of a coin toss with P(head) = p as follows:
• Use rand() function to generate N random numbers uniformly distributed
on [0 1].
• Treat the numbers less than p as tail and the other half as head.
• In this way, you can simulate coin toss experiment N times.
• Count the number of head out of the above N experiments and regard this
as a realization of a random variable X.
(a) Set p = 0:5 and N = 10. Repeat the above procedure 10,000 times.
i. Draw the estimate of PMF of X, i.e., draw P(X = k) for k = 1 2 · · · N

참고자료

· Probability, Random Variables and Random Signal Processing, P.Z. Peebles Jr.,
· McGraw-Hill, 4th ed, 2001.
· MATLAB 객체 지향 프로그래밍 언어, 박전수 역, 아진, 2008.