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)	-
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Should do the basic statistical analyses and interpret the results
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	There is no recommended optional programme component for this course.
COURSE DEFINITION	Simple linear regression, coefficients of correlation and determination, multiple regression, multiple coefficients of correlation and determination, adjusted coefficient of determination, partial correlation. Nonlinear regression models and linearization transformations, hypothesis tests and confidence intervals. Residual analysis; plotting the residuals, multicollinearity, detecting the unequal variances, checking normality assumption, dummy variables, autocorrelation, variable selection methods in multiple regression models and model building.
COURSE CONTENTS	WEEK TOPICS 1st Week Introduction to regression analysis; aims of regression analysis; types of data in regression analysis 2nd Week Simple linear regression; MSE method; model assumptions; estimation of ; estimation, confidence intervals and testing of regression parameters 3rd Week Simple linear regression; MSE method; model assumptions; estimation of ; estimation, confidence intervals and testing of regression parameters 4th Week Multiple regression; MSE method; model assumptions; estimation of ; estimation, confidence intervals and testing of regression parameters 5th Week Multiple coefficient of determination; using multiple regression models for estimation and prediction 6th Week Multiple coefficient of determination 7th Week Multiple coefficient of determination 8th Week MIDTERM 9th Week Model models with quantitative and qualitative variables building; 10th Week Model models with quantitative and qualitative variables building; 11th Week Model models with quantitative and qualitative variables building; 12th Week Residual analysis; plotting the residuals; detecting the unequal variances; 13th Week Multicollinearity; causes of multicollinearity; effects of multicollinearity 14th Week Variable selection methods
RECOMENDED OR REQUIRED READING	"A Second Course in Statistics: Regression Analysis, Fifth Edition ,William MENDENHALL; Terry SINCICH
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Questions/Answers,Problem Solving,Other
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 30 Assignment 1 10 Project 1 10 Total(%) 50 Contribution of In-term Studies to Overall Grade(%) 50 Contribution of Final Examination to Overall Grade(%) 50 Total(%) 100
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No