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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
ISY 504STOCHASTIC PROCESSES3 + 02nd Semester6

COURSE DESCRIPTION
Course Level Master's Degree
Course Type Elective
Course Objective The purpose of this course, students may face certain or uncertain, the resulting problems of quantitative techniques in the face of events that teaches how to solve the
Course Content Basic probability concept, classification of stochastic process, transformation of stochastic process, stochastic differential equations, stochastic integral, average time, correlation and linear systems, Hilbert transformations, least square periods and Fourier series, harmonic analysis of stochastic process, Markov chains, classification of homogen Markov chains, Markov decision process, restructuring theory.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1Probability distributions and learns that the properties of the contours
2Deterministic and stochastic processes, identify and isolate
3Business management purposes is the most appropriate marketing-sales system and processes to receive the task in designing the
4Regarding the planning of the business from the past can make the data
5Based on the analysis of business process and the time can work

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06
LO 001435543
LO 002353534
LO 003534354
LO 004543535
LO 005355353
Sub Total202020212019
Contribution444444

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)14342
Assignments21020
Mid-terms11212
Final examination12020
Presentation / Seminar Preparation21020
Total Work Load

ECTS Credit of the Course






156

6
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2011-2012 Spring1AYŞEGÜL TUŞ


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
ISY 504 STOCHASTIC PROCESSES 3 + 0 1 Turkish 2011-2012 Spring
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Assoc. Prof. Dr. AYŞEGÜL TUŞ atus@pau.edu.tr Course location is not specified. %
Goals The purpose of this course, students may face certain or uncertain, the resulting problems of quantitative techniques in the face of events that teaches how to solve the
Content Basic probability concept, classification of stochastic process, transformation of stochastic process, stochastic differential equations, stochastic integral, average time, correlation and linear systems, Hilbert transformations, least square periods and Fourier series, harmonic analysis of stochastic process, Markov chains, classification of homogen Markov chains, Markov decision process, restructuring theory.
Topics
WeeksTopics
1 Probability, Probability Propositions, Probability Rules
2 Bivariate Probabilities, Bayes Theorem
3 Discrete Random Variables and Their Probability Distributions
4 Continuous Random Variables and Their Probability Distributions
5 Expected Value and Variance of Discrete and Continuous Random Variables
6 Jointly Distributed Random Variables
7 Basic Concepts about Stochastic Processes
8 Binomial Distribution
9 Poisson Distribution
10 Exponential Distribution
11 Markov Process: Basic Concepts
12 Markov Chains in Finite and Countable Cases
13 Queuing Models
14 Queuing Models (continued)
Materials
Materials are not specified.
Resources
ResourcesResources Language
İşletme ve İstatistik için İstatistik, 4. Baskı, Paul Newbold, Çeviren: Ümit Şenesen. Türkçe
Statistics for Business and Economics, Seventh Edition, Pearson, Authors: Paul Newbold, William L. Carlson, Betty Thorne English
Olasılıksal Süreçlere Giriş (Markov Zincirleri), Doç. Dr. H. Ceyhan İnal, Hacettepe Üniversitesi YayınlarıTürkçe
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam20Midterm Exam
Homework20Homework
Attendance to Lesson10Attendance to Lesson
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes