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PROBABILITY AND STATISTICS PROGRAMME COURSE DESCRIPTION

Code Name of the Course Unit Semester In-Class Hours (T+P) Credit ECTS Credit
MAT207 PROBABILITY AND STATISTICS 3 3 3 5

GENERAL INFORMATION

Language of Instruction : Turkish
Level of the Course Unit : BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course : Compulsory
Mode of Delivery of the Course Unit -
Coordinator of the Course Unit Assist.Prof. BİNNUR GÜRÜL
Instructor(s) of the Course Unit Assist.Prof. BAHADIR KOPÇASIZ-Assist.Prof. FERHAT KÜRÜZ-Assist.Prof. ZEHRA CİVAN
Course Prerequisite No

OBJECTIVES AND CONTENTS

Objectives of the Course Unit: Identifies problem in the field of statistic problem and find solution,prerares reports for statistic problem, solving continious random variable problem and normal distributio
Contents of the Course Unit: Introduction of basic statistical concepts, central tendency and variability measures,probability, intermittent and continuous distributions , binom and poisson, continuous distributions and normal distrubituon applications

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)

Know the basic concepts of probability theory.
Use common probability distributions and analyse their properties.
Compute conditional probability distributions and conditional expectations.
Compute distributions by use of transformation techniques and solve problems.
Define and use the properties of Stochastic processes, especially Gaussian and Poisson Processes.

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY

Week Preparatory Topics(Subjects) Method
1 - Introduction of statistic science -
2 - Statstic error,main and sample mass -
3 - Frequency distrubution and histogram -
4 - Aritmetic mean,mode, median -
5 - Change interval, average deviation,variance -
6 - Standart deviation,coefficient of variation -
7 - Introduction of probability -
8 - MID-TERM EXAM -
9 - Conditional probability -
10 - Dependent and independent variables -
11 - Dependent and independent events -
12 - Discrete random variable and binom distribution -
13 - Discrete random variable and poisson distribution -
14 - Continuous random variable and normal distribution -
15 - Preparation for Final exam -
16 - FINAL EXAM -
17 - FINAL EXAM -

SOURCE MATERIALS & RECOMMENDED READING

Mühendislik İstatistiği;Montgomery,Runger,Hubele;Çeviri:Coşkun ÖZKAN,Palme Yayıncılık2017
Matemetiksel İstatistik,Mustafa Aytaç, Ezgi yayınları,Ankara Üniv.yayını,1999
Örnekleme Teorisi ve işletme yönetiminde uygulaması,Orhan İdil,İ.Ü. Yayını,1980
Matemetiksel İstatistiğe giriş,Uğur Korum,Ankara üniversitesi,1971
Yönetimde istatistik teknikler ve örnek olaylar, Orhan İdil,İst. Gelişim Üniv. ,1979

ASSESSMENT

Assessment & Grading of In-Term Activities Number of Activities Degree of Contribution (%) Description
Level of Contribution
0 1 2 3 4 5

CONTRIBUTION OF THE COURSE UNIT TO THE PROGRAMME LEARNING OUTCOMES

KNOWLEDGE

Theoretical

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Gain sufficient knowledge in Mathematics, Science and Industrial Engineering.
3

KNOWLEDGE

Factual

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Analyzes and evaluates existing application areas in the field of Industrial Engineering and develops applications for their solutions.
3

SKILLS

Cognitive

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Analyzes a system, the components of that system, the process of that system, and designs the system by examining it in line with realistic constraints and goals.
5
2
Gains the ability to model and solve engineering problems.
3

SKILLS

Practical

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Identifies the problems that may be encountered in the field of industrial engineering and acquires the ability to choose and apply the appropriate method to be used in problem solving.
3
2
Selects and uses technical tools necessary for industrial engineering applications; uses information technologies effectively.
3
3
Designs experiments, conducts experiments, collects data, analyzes and interprets the results to examine problems in the field of industrial engineering.
4

OCCUPATIONAL

Autonomy & Responsibility

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Gains the ability to work effectively within a team.
4
2
Works effectively individually and takes responsibility.
3

OCCUPATIONAL

Learning to Learn

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Accesses the necessary information for a determined problem and searches for resources for this purpose.
4
2
Has the ability to follow all developments in the field of industrial engineering and constantly renew itself.
3

OCCUPATIONAL

Communication & Social

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Gains oral and written communication skills and speaks at least one foreign language.
1

OCCUPATIONAL

Occupational and/or Vocational

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Has awareness of professional and ethical responsibility.
1
2
Has knowledge about the universal and social effects of industrial engineering applications and reaches solutions by being aware of the importance of an innovative approach in solving engineering problems.
3

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT

Workload for Learning & Teaching Activities

Type of the Learning Activites Learning Activities (# of week) Duration (hours, h) Workload (h)
Lecture & In-Class Activities 14 3 42
Preliminary & Further Study 14 3 42
Land Surveying 0 0 0
Group Work 0 0 0
Laboratory 0 0 0
Reading 0 0 0
Assignment (Homework) 3 5 15
Project Work 0 0 0
Seminar 0 0 0
Internship 0 0 0
Technical Visit 0 0 0
Web Based Learning 0 0 0
Implementation/Application/Practice 0 0 0
Practice at a workplace 0 0 0
Occupational Activity 0 0 0
Social Activity 0 0 0
Thesis Work 0 0 0
Field Study 0 0 0
Report Writing 0 0 0
Final Exam 1 1 1
Preparation for the Final Exam 5 3 15
Mid-Term Exam 1 1 1
Preparation for the Mid-Term Exam 5 2 10
Short Exam 1 2 2
Preparation for the Short Exam 1 3 3
TOTAL 45 0 131
Total Workload of the Course Unit 131
Workload (h) / 25.5 5,1
ECTS Credits allocated for the Course Unit 5,0