C OUR SE SYLLA BUS
YEDITEPE UNIVERSITY
2013/2014-2
FACULTY OF ENGINEERING A ND ARCHITECTUR E
Course Code-Name ES 231 Fundamentals of Probability Theory and Statistics
Section
Section
Section
Section
Section
Section
1:
2:
3:
4:
5:
6:
Lecture:
Lecture:
Lecture:
Lecture:
Lecture:
Lecture:
Section
Section
E-mail Section
Section
Section
Section
123456-
Seval Genç ……………………… sgenc@marmara.edu.tr
Seval Genç ……………………… sgenc@marmara.edu.tr
D. Uğur Şanlı…………………….usanli@yildiz.edu.tr
D. Uğur Şanlı…………………….usanli@yildiz.edu.tr
Ebru Angün………………………eangun@gsu.edu.tr
Ebru Angün………………………eangun@gsu.edu.tr
Course Schedule
Instructors’ Names
Tue
Tue
Tue
Tue
Tue
Tue
14:00-16:00; Thu 16:00-18:00
16:00-18:00; Thu 14:00-16:00
14:00-16:00; (B444) Thu 16:00-18:00 (B444)
16:00-18:00; (B444) Thu 14:00-16:00 (B444)
14:00-16:00; () Thu 16:00-18:00 ()
16:00-18:00; () Thu 14:00-16:00 ()
Textbook &
Supplementary
Materials
TEXT BOOK: Probability & Statistics for Engineers and Scientists, R.E.
Walpole, R.H. Myers, S.L. Myers, and K. Ye, , Prentice Hall, 2007
Recommended
Prerequisites
Math 152
Course Outline
The aim of this course is to introduce fundamentals of Probability Theory to
engineering students. In the course, the theoretical background for
Probability Theory, and the use of probabilistic models and statistical
methodology will be covered, fully. The important balance between the
theory and methodology will be maintained throughout the course,
demonstrating the use of the corresponding techniques through various
applications in different branches of science and engineering.
Midterm Dates
REFERENCES:
 Applied Statistics and Probability for Engineers, D.C. Montgomery, G.C.
Runger, Wiley.
 Probability and Statistics for Engineering and the Sciences, J.L. Devore.
Midterm I : March 18, 2014
Midterm II: April 29, 2014
Grading




Attendance
80 % attendance is required.
Additional Remarks
Quizzes
Midterm I
Midterm II
Final Exam
:
:
:
:
10 %
25 %
25 %
40 %
YEDITEPE UNIVERSITY
C OUR SE SYLLA BUS
FACULTY OF ENGINEERING A ND ARCHITECTUR E
2013/2014-2
Course CodeES 231 Fundamentals of Probability Theory and Statistics
Name
Course
Objectives


Course
Outcomes
To understand the fundamentals of probability theory and to be able to apply
them.
To understand the fundamentals of descriptive statistics and to be able to use
them.
an ability to apply knowledge of mathematics, science and engineering

an ability to design and conduct experiments, as well as to analyze and interpret data
 
Indicates the
level of
satisfaction of an ability to design a system, component or process to meet desired needs
the course for
the outcomes an ability to function on multi-disciplinary teams
listed.
 
 
: Not
an ability to identify, formulate, and solve engineering problems
 
: Low Level
an understanding of professional and ethical responsibility
 
an ability to communicate effectively
 
the broad education is necessary to understand the impact of engineering solutions in a
global and societal context
 
a recognition of the need for, and an ability to engage in life-long learning
 
a knowledge of contemporary issues
 
an ability to use the techniques, skills, and modern engineering tools necessary for
engineering practice
 
Applicable
of Satisfaction
: High Level
of Satisfaction
COURSE PLAN
Week
Topics
1
3-7/02
Introduction to Probability and Statistics. Statistical Experiments. Outcomes.
Events. Sample Space. Set Theory.
2.1, 2.2
2
10-14/2
Interpretations and Axioms of Probability. Basic Theorems of Probability. Finite
Sample Spaces. Counting Techniques. Multiplication Rule. Permutations.
Combinations. Sampling With and Without Replacement.
2.3, 2.4, 2.5
3
17-21/2
Independence of Events. Conditional Probability. Bayes’ Theorem.
2.6, 2.7, 2.8
4
Discrete Random Variables. Probability Function. Distribution Function. Mean and
Variance.
3.1, 3.2, 4.1 (discrete), 4.2 (discrete),
24-28/2
5-6
3-14/3
Special Discrete Distributions (Uniform, Bernoulli, Binomial, Hypergeometric,
Geometric, Negative Binomial, Poisson).
5.1, 5.2, 5.3, 5.4, 5.5, 5-6
7
17-21/3
Review
Midterm 1
8
24-28/3
Continuous Random Variables. Probability Density Function.
3.3, 4.1 (cont.), 4.2 (cont.)
9
1-4/4
Special Continuous Distributions (Uniform, Normal, Normal Approximation to
Binomial, Gamma, Exponential).
6.1, 6.2, 6.3, 6.4, 6.5, 6-6, 6.7
10
7-11/4
Special Continuous Distributions (Uniform, Normal, Normal Approximation to
Binomial, Gamma, Exponential).
11-12
14-25/4
Joint, Marginal and Conditional Distributions. Covariance and Correlation.
Conditional Mean and Variance. Independence of Random Variables.
3.4, Rest of chapter 4
13
28/4-2/5
Review
Midterm 2
14
5-9/5
Introduction to Statistics and Data Analysis
15
12-16/5
Hypothesis Testing and Review Problems