STOCHASTIC PROCESSES in HEALTH SYSTEMS

AIM

This course aims to introduce the basic stochastic processes used to deal with the uncertainties frequently encountered in healthcare systems and to teach the basic concepts and methods to be used to model and analyze these processes.

CONTENT

This course contains; Introductıon to the course and ınformatıon about the course,Probabılıty theory-General revıew,Condıtıonal probabılıty and condıtıonal expectatıon,Introductıon to stochastıc processes and markov chaıns,Dıscrete-tıme markov chaıns-1,Dıscrete-tıme markov chaıns-2,Dıscrete-tıme markov chaıns-3,Exponentıal dıstrıbutıon and poısson processes-1,Exponental dıstrıbutıon and poısson processes-2,Exponentıal dıstrıbutıon and poısson processes-3,Contınuous tıme markov chaıns-1,Contınuous tıme markov chaıns-2,Queuıng systems-1,Queuıng systems-2.

1. 1

   Define queuing theory.

   Taught by: Discussion Method, Question - Answer Technique, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Project Task

2. 2

   Analyze Markov chain models.

   Taught by: Discussion Method, Question - Answer Technique, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Project Task

3. 3

   Apply the exponential distribution and its relationship to the Poisson process.

   Taught by: Discussion Method, Question - Answer Technique, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Project Task

4. 4

   Recognize the techniques used to model uncertainities faced in healthcare systems.

   Taught by: Discussion Method, Question - Answer Technique, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Project Task

5. 5

   Distinguish between deterministic and random processes.

   Taught by: Discussion Method, Question - Answer Technique, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Project Task

WEEKLY PLAN

1. WEEK 1

   Introductıon to the course and ınformatıon about the course

   Preparation: Introduction to Probability Models - Overall examination.

2. WEEK 2

   Probabılıty theory-General revıew

   Preparation: Introduction to Probability Models - Chapter 1

3. WEEK 3

   Condıtıonal probabılıty and condıtıonal expectatıon

   Preparation: Introduction to Probability Models - Chapter 2

4. WEEK 4

   Introductıon to stochastıc processes and markov chaıns

   Preparation: Introduction to Probability Models - Chapter 4

5. WEEK 5

   Dıscrete-tıme markov chaıns-1

   Preparation: Introduction to Probability Models - Bölüm 5

6. WEEK 6

   Dıscrete-tıme markov chaıns-2

   Preparation: Introduction to Probability Models - Chapter 5

7. WEEK 7

   Dıscrete-tıme markov chaıns-3

   Preparation: Introduction to Probability Models - Chapter 5

8. WEEK 8

   Exponentıal dıstrıbutıon and poısson processes-1

   Preparation: Introduction to Probability Models - Chapter 6

9. WEEK 9

   Exponental dıstrıbutıon and poısson processes-2

   Preparation: Introduction to Probability Models - Chapter 6

10. WEEK 10

    Exponentıal dıstrıbutıon and poısson processes-3

    Preparation: Introduction to Probability Models - Chapter 6

11. WEEK 11

    Contınuous tıme markov chaıns-1

    Preparation: Introduction to Probability Models - Chapter 7

12. WEEK 12

    Contınuous tıme markov chaıns-2

    Preparation: Introduction to Probability Models - Chapter 7

13. WEEK 13

    Queuıng systems-1

    Preparation: Introduction to Probability Models - Chapter 9

14. WEEK 14

    Queuıng systems-2

    Preparation: Introduction to Probability Models - Chapter 9

ASSESSMENT

• Rate of Midterm Exam to Success50%
• Rate of Final Exam to Success50%

WORKLOAD

READING

• Introduction to Probability Models by Sheldon Ross, Academic Press

TEACHING STAFF

• Assist.Prof. Rüçhan Melisa DENİZ ÖZGENCOORDINATOR
• Assist.Prof. Rüçhan Melisa DENİZ ÖZGEN