1. Find the method of moments estimator for p for the Bernoulli distribution. (see page 78) 2. Find the maximum likelihood estimator for p for the Bernoulli distribution. Show your work. 3. Find the maximum likelihood estimator for p for the Binomial distribution. Show your work.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
icon
Related questions
Question
1. Find the method of moments estimator for p for the Bernoulli distribution. (see page 78)
2. Find the maximum likelihood estimator for p for the Bernoulli distribution. Show your work.
3. Find the maximum likelihood estimator for p for the Binomial distribution. Show your work.
This is tricky because of our standard notation. Generally, we think of the sample size as n, but in the binomial
distribution we have already defined n as the number of trials from which you count then number of successes X. Let's
keep that definition for n for now, and use the letter m to represent your sample size. Note, that n and m are fixed. The
value for p is the one you're trying to find an estimate for.
(For clarification - ignore this if it doesn't help. Let's say you're testing lightbulbs in packs of 4 and counting the number
of defective bulbs in the set. In this case n=4 and X can take on any integer from 0 to 4. But now you do this testing 30
times in a day, meaning you test 30 packs of 4 lightbulbs. In this case m=30. So at the end of the day, you have 30
values, each of which is between 0 and 4. And question 3 is asking you how to use this data to come up with an
estimate for p. You need to use the generic variables n, m, p when solving problem 3, but I was hoping that this concrete
example would help put things in context.)
Transcribed Image Text:1. Find the method of moments estimator for p for the Bernoulli distribution. (see page 78) 2. Find the maximum likelihood estimator for p for the Bernoulli distribution. Show your work. 3. Find the maximum likelihood estimator for p for the Binomial distribution. Show your work. This is tricky because of our standard notation. Generally, we think of the sample size as n, but in the binomial distribution we have already defined n as the number of trials from which you count then number of successes X. Let's keep that definition for n for now, and use the letter m to represent your sample size. Note, that n and m are fixed. The value for p is the one you're trying to find an estimate for. (For clarification - ignore this if it doesn't help. Let's say you're testing lightbulbs in packs of 4 and counting the number of defective bulbs in the set. In this case n=4 and X can take on any integer from 0 to 4. But now you do this testing 30 times in a day, meaning you test 30 packs of 4 lightbulbs. In this case m=30. So at the end of the day, you have 30 values, each of which is between 0 and 4. And question 3 is asking you how to use this data to come up with an estimate for p. You need to use the generic variables n, m, p when solving problem 3, but I was hoping that this concrete example would help put things in context.)
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 2 steps with 2 images

Blurred answer
Similar questions
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman