This preview shows pages 1–2. Sign up to view the full content.
CE 93 Spring 2011
Prof. Joan Walker
1
CE 93 Lab 11 (Apr 13, 2011)
Part I) Illustration of maximum likelihood estimation
The number of accidents occurring weekly on a particular stretch of a highway has a Poisson
distribution. From historical data we randomly picked ten weeks
’
records, as follows:
4 3 5 0 2 4 6 1 3 4
1. What are the likelihood function and loglikelihood function?
2. Determine the maximum likelihood estimator of the parameter
λ
.
3. Plot L(
λ
) and LL(
λ
) respectively against
λ
, for values of
λ
ranging from 1 to 10. You will observe
the log transformation does not change the point where the maximum value in the respective
functions is achieved.
Part II) Confidence interval of unknown parameters of Normal distribution
Suppose that we know that the concrete cube compressive strength (in N/mm^2) at 28 days is
normally distributed, and you measured ten such cubes whose compressive strengths are 64.9,
48.6, 69.1, 78.2, 55.1, 70.6, 74.5, 46.1, 47.6, 67.7.
1.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
This is the end of the preview. Sign up
to
access the rest of the document.
This note was uploaded on 06/02/2011 for the course CIV ENG 93 taught by Professor Staff during the Spring '08 term at University of California, Berkeley.
 Spring '08
 Staff

Click to edit the document details