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

Course General Introduction Information

Course Code:

MTH301

Course Name:

Probability and Statistics

Course Semester:

Fall

Course Credits:

ECTS

Language of instruction:

Course Requirement:

Does the Course Require Work Experience?:

Type of course:

Necessary

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 :

Assoc. Prof. HATİCE ESRA ÖZKAN UÇAR

Course Lecturer(s):

Prof. Dr. Murat ALAN

Course Assistants:

Course Purpose and Content

Course Objectives:	In this course, the student is expected to understand the basic arguments of probability and statistics theory and to be competent enough to apply them.
Course Content:	Probability types and statistical analysis approaches

Learning Outcomes

The students who have succeeded in this course;
1) Calculates permutations and combinations.
2) Understands what a random variable is.
3) Defines basic probability terminologies such as experiment, result, sample space, event.
4) Defines a probability distribution and probability density function.
5) Understands the concept of mathematical expectation.
6) Explains the concepts of joint, marginal and conditional distribution.
7) Understands when/where specific probability distributions should be used.
8) It defines various special continuous distributions.
9) Can solve problems independently.

Course Flow Plan

Week	Subject	Related Preparation
1)	Sets, Combinatoric Methods, Binomial Coefficients	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
2)	Sample Space, Event, Probability of an Event, Some Probability Rules	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
3)	Conditional Probability, Independent Events, Bayes Theorem	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
4)	Random Variables, Discrete Probability Distribution	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
5)	Continuous Random Variables	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
6)	Common Distributions	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
7)	Marginal and Conditional Distributions	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
8)	Mathematical Expectation of a Random Variable, Moments	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
9)	Chebyshev's Theorem, Moment Generating Functions	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
10)	Product Moments, Conditional Expectation	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
11)	Discrete Uniform Distribution, Bernolli Distribution, Binomial Distribution	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
12)	Negative Binomial and Geometric Distributions, Hypergeometric Distribution	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
13)	Poisson Distribution, Uniform Distribution	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
14)	Normal Distribution, Normal Approach to Binomial Distribution, Normal Approach to Poisson Distribution	I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
15)	Finals Week
16)	Finals Week
17)	Finals Week

Sources

Course Notes / Textbooks:	Murray R. Spiegel, John J. Schiller, and R. Alu Srinivasan, Probability and Statistics, Schaum's Outline Series, Third Edition, New York, ISBN: 978-0-07-154426-9, 2009. I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.
References:	Murray R. Spiegel, John J. Schiller, and R. Alu Srinivasan, Probability and Statistics, Schaum's Outline Series, Third Edition, New York, ISBN: 978-0-07-154426-9, 2009. I. Miller, M. Miller, John E. Freund's Mathematical Statistics with Applications, Pearson Prentice Hall, Seventh Edition, New Jersey, ISBN: 0978-0-13-124646-1, 2004.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Medium	3 Highest

	Program Outcomes	Level of Contribution
1)	Adequate knowledge in mathematics, science, and related engineering discipline; ability to use theoretical and practical knowledge in these areas in complex engineering problems.
2)	An ability to detect, identify, formulate, and solve complex engineering problems; the ability to select and apply appropriate analysis and modelling methods for this purpose.
3)	An ability to design a complex system, process, device, or product to meet specific requirements under realistic constraints and conditions; the ability to apply modern design methods for this purpose.
4)	An ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems in engineering applications.
5)	An ability to use information technologies effectively.
6)	Ability to design, conduct experiments, collect data, analyse, and interpret results to investigate complex engineering problems or discipline-specific research topics.
7)	Ability to work effectively in disciplinary and multidisciplinary teams; ability to work individually.
8)	Ability to communicate effectively in oral and written Turkish.
9)	Knowledge of at least one foreign language.
10)	Ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give clear and understandable instructions.
11)	Awareness of the necessity of lifelong learning; ability to access information, follow developments in science and technology and ability to renew themselves.

Learning Activity and Teaching Methods

Bireysel çalışma ve ödevi
Course
Homework
Problem Çözme

Measurement and Evaluation Methods and Criteria

Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama)
Homework
Uzman / Jüri Değerlendirmesi

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	1	% 20
Midterms	1	% 30
Final	1	% 40
Kanaat Notu	1	% 10
total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
total		% 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Aktiviteye Hazırlık	Aktivitede Harçanan Süre	Aktivite Gereksinimi İçin Süre	Workload
Course Hours	17	2			34
Study Hours Out of Class	14	2			28
Midterms	1	48			48
Final	1	48			48
Total Workload					158