CE310 Probability and Statistics in Civil Engineering
Spring 2011
Catalog Description: (3 units) Statistical decision theory and its application in civil engineering,
identification and modeling of non-deterministic problems in civil engineering and the treatment
thereof relative to engineering design and decision making, statistical reliability concepts.
Prerequisite(s): MATH 129; Advanced standing.
Course Objectives: To develop a basic concepts on probability and different types of distribution
functions and their applications in civil engineering; determination of distributions and parameters
from observation data; randomness in response variables including regression analysis; reliability
evaluation procedures and simulation techniques.
ABET outcomes:
Primary
A. Apply mathematics, science and engineering principles
B. Ability to design and conduct experiments and interpret data
E. Ability to identify, formulate, and solve engineering problems
Secondary
C. Ability to design a system, component, or process to meet desired needs
H. The broad education necessary to understand the impact of engineering solutions in a
global context
K. Ability to use the techniques, skills, and modern engineering tools necessary for
engineering practice
L. Pass the FE exam as the first step towards professional registration
M. Be proficient in the major areas of civil engineering
Instructor:
Class time & place:
Office Hours:
Review Sessions:
Office:
e-mail:
Ajoy Kumar Das
MWF 11:00-11:50AM @ HARVILL 404
MW 1:00-2:00PM; F 3:30-4:30PM
TBA
CE 318F
akdas@email.arizona.edu
Textbook: Probability, Reliability, and Statistical Methods in Engineering Design, by Achintya
Haldar and Sankaran Mahadevan, John Wiley and Sons, Inc., November 1999, ©2000, ISBN 978-0471-33119-3
Evaluation
Homeworks
Tests (2)
Final Exam
Exams will be open book/open note. Dates and syllabus of the
class.
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15%
50%
35%
two tests will be announced in the
Homework assignments and due dates will be announced in the class. Homework problems should be
done neatly using only one side of engineering paper and should be turned in the class. No late
assignments will be accepted.
Tentative Outline
1
2
Week
Starts
1/12
1/17
3
4
1/24
1/31
5
2/7
6
7
8
2/14
2/21
2/28
9
3/7
10 3/14
11 3/21
12 3/28
13 4/4
14 4/11
15 4/18
16 4/25
17 5/2
Topic
Reading
Basic Concept of Reliability
Mathematics of Probability – Introduction, Introduction to Set Theory,
Axioms of Probability, Multiplication Rule
Theorem of Total Probability, Baye’s Rule
Modeling Uncertainty – Introduction, Steps in Quantifying Randomness,
Analytical Models to Quantify Randomness
Commonly used Probability Distributions – Introduction, Continuous
Random Variables
Discrete Random Variables
Examples on Probability Distributions
Test I (2/28 through Probability Distributions). Determination of
Distributions and Parameters from Observed Data – Introduction,
Determination of Probability Distribution: Probability papers,
construction of a Probability Paper
Statistical Tests, Estimation of Parameters of a Distribution, Interval
Estimation of Mean and Variance
Spring Break
Randomness in Response Variables – Introduction, Known Functional
Relationship Between the Response and a Single Basic Random
Variable, Response as a Known Function of Multiple Random Variables
Partial and Approximate Solutions, Regression Analysis
Examples on Randomness in Response Variables
1.1-1.7
2.1, 2.2,2.3,
2.4
2.5,2.6
3.1,3.2,3.3
Test II (3/14 through Randomness in Response Variables)
Fundamentals of Reliability Analysis - Introduction, Deterministic and
Probabilistic Approaches, Risk and Safety Factor Concept
Risk-Based Design Concept and the Development of the Risk-Based
Design Format - Load and Resistance Normal Variable: Single or
Multiple Load Case
Load and Resistance Lognormal Variables: Single or Multiple Load
Case, Simulation Techniques - Introduction
Monte Carlo Simulation Technique
Final Exam: Thursday May 9, 2011 10:30 a.m. - 12:30 p.m. in HARVILL 404
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4.1,4.2
4.3
4.1,4.2,4.3
5.1,5.2.1,
5.2.2
5.2.3,5.3,
5.4
6.1,6.2,6.3
6.4,6.6
6,1,6.2,6.3
6.4,6.6
7.1,7.2,7.3
7.4,7.4.1,
7.4.2
7.4.3,7.4.4,
9.1
9.2
Academic Integrity
Principle Integrity and ethical behavior are expected of every student in all academic work. This
Academic Integrity principle stands for honesty in all class work, and ethical conduct in all labs and
clinical assignments. This principle is furthered by the student Code of Conduct and disciplinary
procedures established by ABOR Policies 5-308 through 5-404, all provisions of which apply to all
University of Arizona students.
This Code of Academic Integrity (hereinafter "this Code") is intended to fulfill the requirement
imposed by ABOR Policy 5-403.A.4 and otherwise to supplement the Student Code of Conduct as
permitted by ABOR Policy 5-308.C.1.
Failure to follow the code of academic integrity will result in failing the course and be reported
to the Dean of Students’ office.
Prohibited Conduct: Conduct prohibited by this Code consists of all forms of academic dishonesty,
including, but not limited to:
1 Cheating, fabrication, facilitating academic dishonesty, and plagiarism as set out and defined in the
Student Code of Conduct, ABOR Policy 5-308-E.6, E.10, and F.1
2 Submitting an item of academic work that has previously been submitted without fair citation of the
original work or authorization by the faculty member supervising the work.
3 Violating required professional ethics rules contained or referenced in the student handbooks
(hardcopy or online) of undergraduate or graduate programs, or professional colleges.
4 Violating health, safety or ethical requirements to gain any unfair advantage in lab(s) or clinical
assignments.
5 Failing to observe rules of academic integrity established by a faculty member for a particular
course.
6 Attempting to commit an act prohibited by this Code. Any attempt to commit an act prohibited by
these rules shall be subject to sanctions to the same extent as completed acts.
Student Responsibility
Students engaging in academic dishonesty diminish their education and bring discredit to the
academic community. Students shall not violate the Code of Academic Integrity and shall avoid
situations likely to compromise academic integrity. Students shall observe the generally applicable
provisions of this Code whether or not faculty members establish special rules of academic integrity
for particular classes. Students are not excused from complying with this Code because of faculty
members’ failure to prevent cheating.
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ABET 2010 Criteria Course Classification Form
Course Number CE 310
Course Name Probability and Statistics in Civil Engineering
Required? Circle: YES / NO
Semester/Instructor Spring 2011 – Ajoy Kumar Das
Homework Frequency weekly
Exam Frequency Two (2) midterms & one (1) final
Course Project?
Circle: YES / NO
Labs or Case Studies?
Circle: YES / NO
For each of the following ABET outcome criteria, please list the level (High, Medium, Low, or blank if not applicable) contained in this course. The
criteria descriptions that will be used by the College in the ABET evaluation are attached. Please describe the relevant course activities that you can use
to justify why you think your course meets the criteria. No course is expected to address all of these criteria and it would be rare to have more
than 2 or 3 criteria at a high level (except a capstone course) Be conservative in your judgment. For the ABET evaluation, we will assess student
performance for criteria that are judged High. If you judge your course as High in a criteria, then the course should include a large percentage of effort
(class time, homework, projects) devoted to the criteria. Note that 2 extra table entries are available for departments to specify their own criteria.
Outcome criteria
Level
Relevant Activities
HML
A. Apply mathematics, science and
engineering principles
B. Ability to design and conduct
experiments and interpret data
C. Ability to design a system, component,
or process to meet desired needs
D. Ability to function on multidisciplinary
teams
E. Ability to identify, formulate, and solve
engineering problems
F. Understanding of professional and
ethical responsibility
G. Ability to communicate effectively
H
H
Application of principles of mathematics and
engineering to quantify uncertainty
Mathematical modeling of experimental data
L
Developing and understanding relationship between
safety factor and risk in design problems
H
Simple design problems satisfying pre-selected risk
H. The broad education necessary to
understand the impact of engineering
solutions in a global context
I. Recognition of the need for and an
ability to engage in life-long learning
J. Knowledge of contemporary issues
L
Different design practices and uncertainty in them in
K. Ability to use the techniques, skills, and
modern engineering tools necessary for
engineering practice
L. Pass the FE exam as the first step
towards professional registration
M. Be proficient in the major areas of civil
engineering
M
different countries
codes
L
Be familiar with reliability and statistics-related issues
M
Be familiar with risk-based design codes
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Develop an appreciation of recent risk-based design