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•           Information on Degree Programmes

COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Probability And Statistics I ENM   243 3 3 3 4

 Prerequisites and co-requisites Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Prof.Dr. Rızvan EROL
Instructors
 Dr. Öğr. Üyesi SELMA TOKER KUTAY 1. Öğretim Grup:A

Assistants
Goals
Learn the basic concepts of permutation, combination, probability and random variables and their properties. Learn to design and analyze the data
Content
Permutation, combination, probability, sampling, measures of central tendency ,random variables

Learning Outcomes
1) Solve the problems of permutation and combination
2) Use the probability of an event, probability axioms, and some of the rules of probability
3) Apply conditional probability, independent events, Bayes theorem
4) Organize and analyze data
5) Understand measures of central tendency and dispersion measures
6) Know the concept of a random variable, the distribution of a random variable
7) Describe the expected value of a random variable, the variance and their properties
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Has sufficient background on topics related to mathematics, physical sciences and industrial engineering.
2
Gains ability to use the acquired theoretical knowledge on basic sciences and industrial engineering for describing, formulating and solving an industrial engineering problem, and to choose appropriate analytical and modeling methods.
3
Gains ability to analyze a service and/or manufacturing system or a process and describes, formulates and solves its problems .
4
Gains ability to choose and apply methods and tools for industrial engineering applications.
5
Can collect and analyze data required for industrial engineering problems ,develops and evaluates alternative solutions.
6
Works efficiently and takes responsibility both individually and as a member of a multi-disciplinary team.
7
Can access information and to search/use databases and other sources for information gathering.
8
Appreciates life time learning; follows scientific and technological developments and renews himself/herself continuously.
9
Can use computer software in industrial engineering along with information and communication technologies.
10
Can use oral and written communication efficiently.
11
Uses English skills to follow developments in industrial engineering and to communicate with people in his/her profession.
12
Has a conscious understanding of professional and ethical responsibilities.
13
Has a necessary consciousness on issues related to job safety and health, legal aspects of environment and engineering practice.
14
Becomes competent on matters related to project management, entrepreneurship, innovation and has knowledge about current matters in industrial engineering.

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Sample spaces and events Source reading
4 Ordered and unordered disruptions, Binomial expansion Source reading
5 Probability of an event, Probability axioms, Source reading
7 Independent events, Bayes theorem Source reading
9 Methods of sample selection Source reading
10 Data Organization, Frequency Distribution, Graphical Representations Source reading
11 Measures of Central Tendency, Measures of Dispersion Source reading
12 Measure of skewness and kurtosis, Coefficient of variation Source reading
13 Distribution of Discrete Random Variable Source reading
14 Distribution of Continous Random Variable Source reading
15 Expected Value, Variance and their properites Source reading