Energy Systems Engineering (English)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

General course introduction information

Course Code:

MATH265

Course Name:

Probability & Statistics I

Course Semester:

Fall

Course Credits:

Theoretical	Practical	Credit	ECTS
3	0	3	5

Language of instruction:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

Compulsory

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Dr.Öğr.Üyesi MESERET TUBA GÜLPINAR

Course Lecturer(s):

Dr.Öğr.Üyesi ASUMAN ÖZER

Course Assistants:

Course Objective and Content

Course Objectives:

The aim of the course is to gain basic knowledge and abilities to the students about Combinatorial methods; product rule, permutation, combination. Probability; probability axioms, conditional probability, Bayes formula. Random variable; distribution function, probability function, Chebyshev inequality. Discrete and continuous distributions; uniform, Bernoulli, Poisson, geometric, hypergeometric, normal, exponential, gamma and beta distributions. Generating functions.

Course Content:

Combinatorial methods; product rule, permutation, combination. Probability; probability axioms, conditional probability, Bayes formula. Random variable; distribution function, probability function, Chebyshev inequality. Discrete and continuous distributions; uniform, Bernoulli, Poisson, geometric, hypergeometric, normal, exponential, gamma and beta distributions. Generating functions.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Solve engineering problems using probability theory.
2) Solve engineering problems using statistics.
3) Formulate probabilistic and statistical models of real life problems.
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week	Subject	Related Preparation
1)	Set Theory, Random Variable, Sample Space, Important Theorems on Probability, Conditional Probability, Bayes’ Theorem, Tree Diagrams, Permutations, Combinations, Binomial Coefficients, Stirlings Approximation,Discrete and Continuous Probability Distributions, Mathematical Expectation,Variance and Standard Deviation, Joint Distributions, Normal , Binomial, Poisson, Multinomial, Hypergeometric etc. Distributions	Bulunmamaktadır.

Sources

Course Notes / Textbooks:	Probability and Statistics for Engineers and Scientists, Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, Pearson Ed. ISBN 13: 978-0-321-62911-1
References:	Lecture Notes- Ders notları

Course-Program Learning Outcome Relationship

Learning Outcomes	1	2	3
Program Outcomes
1) Closed Department

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Closed Department

Learning Activity and Teaching Methods

Lesson
Reading
Problem Solving
Q&A / Discussion

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Midterms	2	% 50
Final	1	% 50
total		% 100
PERCENTAGE OF SEMESTER WORK		% 50
PERCENTAGE OF FINAL WORK		% 50
total		% 100

Workload and ECTS Credit Grading

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	15	3	45
Study Hours Out of Class	15	3	45
Midterms	2	15	30
Final	1	20	20
Total Workload			140