PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
ISY 504	STOCHASTIC PROCESSES	3 + 0	2nd Semester	7,5

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

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

COURSE'S CONTRIBUTION TO PROGRAM

	PO 01	PO 02	PO 03	PO 04	PO 05	PO 06
LO 001	4	3	5	5	4	3
LO 002	3	5	3	5	3	4
LO 003	5	3	4	3	5	4
LO 004	5	4	3	5	3	5
LO 005	3	5	5	3	5	3
Sub Total	20	20	20	21	20	19
Contribution	4	4	4	4	4	4

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Hours for off-the-classroom study (Pre-study, practice)	14	4	56
Assignments	2	15	30
Mid-terms	1	12	12
Final examination	1	25	25
Presentation / Seminar Preparation	2	15	30
Total Work Load ECTS Credit of the Course			195 7,5

COURSE DETAILS

Select Year

Course Details

Course Code	Course Title	L+P Hour	Course Code	Language Of Instruction	Course Semester
ISY 504	STOCHASTIC PROCESSES	3 + 0	1	Turkish	2023-2024 Spring

Course Coordinator	E-Mail	Phone Number	Course Location	Attendance
Assoc. Prof. Dr. AYŞEGÜL TUŞ	atus@pau.edu.tr		İİBF B0009	%70

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

Weeks	Topics
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

Resources	Resources 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 Yayınları	Türkçe

Course Assessment

Assesment Methods	Percentage (%)	Assesment Methods Title
Final Exam	50	Final Exam
Midterm Exam	50	Midterm Exam

L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes

Prospective Student