TYPE OF COURSE UNIT	Elective Course
LEVEL OF COURSE UNIT	Master's Degree With Thesis
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	10
NAME OF LECTURER(S)	Professor Kumru Didem Atalay Assistant Professor Pelin Toktaş
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) will have an ability to interpret statistical data sets by using numerical and graphical techniques. 2) will have an ability to learn the probability definition and its rules to be able to solve problems. 3) will have an ability to learn the concept of random variables and their probability and distribution functions. 4) will have an ability to choose suitable probability distributions to apply and interrelate with the real life problems. 5) will have an ability to describe the basic concepts of statistics (population, sample, random sample, sampling distribution etc.) 6) will have an ability on using sampling distributions in confidence intervals and sampling distributions, gaining ability of statistical inference. 7) will have an ability on determining relationship between variables in research studies.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	None
COURSE DEFINITION	Topics of statistics and methods, units, mode, population, data analysis, central tendency measurements, sampling and sampling methods, sampling distributions. Estimation of the distribution parameters. Statistical estimation, statistical decision theory and hypothesis tests. Analysis of variance. Regression and correlation analysis.
COURSE CONTENTS	WEEK TOPICS 1st Week Probability, random variables and distributions 2nd Week Expected value and moments 3rd Week Basic discrete distributions 4th Week Basic continuous distributions 5th Week Random Sampling, Some Important Statistics 6th Week Concept of Sampling distribution, Sampling Distributions of Means and S2 7th Week t-Distribution, F-Distribution 8th Week Midterm Exam 9th Week One- and Two- Sample Hypothesis Testing (for a Variance and the Ratio of Variances), Maximum Likelihood Estimation 10th Week Hypothesis Testing, Type I and II Errors. Usage of P-Value, 11th Week One- and Two- Sample Hypothesis Testing (for a Mean and Mean Differences) 12th Week Simple Linear Regression and Correlation 13th Week Analysis of Variance Application Lack-of-fit Test 14th Week Introduction to Multivariate Regression Analysis. Quality engineering applications. 15th Week
RECOMENDED OR REQUIRED READING	Walpole R.E., Myers R.H. Myers Sh. L. Ye K. Probability and Statistics or Engineers and Scientists Prentice Hall. 7th edition. Kara, İ., Olasılık, Bilim Teknik Yayınevi, İstanbul, 2000.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Discussion,Questions/Answers,Problem Solving,Other
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 30 Assignment 4 10 Quiz 4 20 Attendance 14 5 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 4 4 16 Individual or group work 14 12 168 Preparation for Final exam 1 20 20 Course hours 14 3 42 Preparation for Midterm exam 1 20 20 Laboratory (including preparation) Final exam 1 2 2 Homework 4 6 24 Total Workload 294 Total Workload / 30 9,8 ECTS Credits of the Course 10
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No