TYPE OF COURSE UNIT	Compulsory Course
LEVEL OF COURSE UNIT	Bachelor's Degree
YEAR OF STUDY	2
SEMESTER	Third Term (Fall)
NUMBER OF ECTS CREDITS ALLOCATED	6
NAME OF LECTURER(S)	Assistant Professor Merve Uzuner Assistant Professor Asiye Özge Dengiz
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Can understand the importance of probability in Industrial Engineering 2) Have the ability to interpret and apply the numerical and graphical methods which are used in summarizing the statistical data sets 3) Have the ability of problem solving by learning the definition and rules of probability 4) Learn and apply the concepts of random variables and their probability and distribution functions 5) Have the ability to choose and apply the suitable probability distribution for a problem and to be able to interrelate with the real life problems, as well. 6) Have the ability to determine the probability distributions for the functions of random variables and to be able to interrelate with sampling distributions as well. 7) Have the ability to describe the basic concepts of statistics (population, sample, ramdom sample, sampling distribution etc.)
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	None
COURSE DEFINITION	Probability concept and basic theorems of probability. Independence, conditional probability and Bayes' rule. Random variable and functions. Considerable discrete and continuous distributions. Distributions of random variables' functions. Subject of statistics and its method. Unit, population, data analysis, central tendency measurements. Sampling and sampling methods, sampling distributions.
COURSE CONTENTS	WEEK TOPICS 1st Week Displays of Data Sets and Calculations of Some Important Statistics 2nd Week Fundamentals of Probability 3rd Week Definition of Probability, Conditional Probability, Bayes' Theorem and Independent Events 4th Week Concept of Random Variable, Probability Distributions 5th Week Discrete and Continuous Probability Distributions 6th Week Joint Probability Distributions, Statistical Independence 7th Week Mathematical Expectation, Variance and Covariance 8th Week Some Discrete Probability Distributions 9th Week Midterm 10th Week Some Continuous Probability Distributions 11th Week Fuctions of Random Variables, Distribution Function Technique 12th Week Change of Variables Techique (For one and two random variables) 13th Week Moment Generating Function Technique, Definition of Random Sampling 14th Week Concept of Random Sampling, Sampling Distributions for Some Statistics
RECOMENDED OR REQUIRED READING	(1) Walpole R.E., Myers R.H. Myers Sh. L. Ye K. Probability and Statistics or Engineers and Scientists Prentice Hall. 7th edition; (2) İ. Kara. Olasılık, Bilim Teknik, 2000 (3) Akdeniz F. "Olasılık ve İstatistik", Nobel Kitabevi, 13. Baskı, 2007. (4) Erbaş S. O. "Olasılık ve İstatistik", Gazi Kitabevi.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Discussion,Questions/Answers,Other
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 35 Assignment 2 5 Quiz 6 25 Total(%) 65 Contribution of In-term Studies to Overall Grade(%) 65 Contribution of Final Examination to Overall Grade(%) 35 Total(%) 100
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 2 2 Preparation for Quiz 3 10 30 Individual or group work 14 1 14 Preparation for Final exam 1 30 30 Course hours 14 4 56 Preparation for Midterm exam 1 30 30 Laboratory (including preparation) 0 0 0 Final exam 1 2 2 Homework 4 3 12 Total Workload 176 Total Workload / 30 5,86 ECTS Credits of the Course 6
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No