Akademik Dersler - Tanıtım


Code - Course Title	İST333 - Regression Analysis
Course Type	Required Courses
Language of Instruction	Türkçe
Laboratory + Practice	4+0
ECTS	6.0
Course Instructor(s)	PROFESÖR DOKTOR YELİZ MERT KANTAR
Mode of Delivery	The mode of delivery of this course is Face to face
Prerequisites	There is no prerequisite or co-requisite for this course.
Courses Recomended	There is no recommended optional programme component for this course.
Required or Recommended Resources	Introduction to linear regression analysis, Montgomery DC., Peck E.A., Vining G.G.,Gujarati, D. N., & Porter, D. C. (2009). Basic Econometrics (5th ed.). McGraw-Hill Education.
Recommended Reading List	Kleinbaum, D. G., Kupper, L. L., Muller, K. E., Applied Regression Analysis and Other Multivariate Methods, 3rd Edition, Duxbury Press, 1998.
Assessment methods and criteria	2 midterms 1 final exam
Work Placement	Not suitable for this course.
Sustainability Development Goals

Weeks	Topics
Week - 1	Conditional Expectation and Regression
Week - 2	Ordinary Least Squares (LSM) Estimators with Simple Linear Regression Models and Parameters
Week - 3	Assumptions of Linear Regression; Properties of the OLS Estimators
Week - 4	Gauss-Markov Theorem
Week - 5	Hypothesis Testing and Confidence Intervals in Simple Linear Regression
Week - 6	Coefficient of Determination
Week - 7	Multiple Linear Regression Model in Matrix Notation
Week - 8	Hypothesis Testing and Confidence Intervals in Multiple Linear Regression
Week - 9	EN: Dummy Variable
Week - 10	Checking of Assumptions (Residual Analysis)
Week - 11	Multicollinearity
Week - 12	Selection of variable
Week - 13	EN:Definition and Meaning of Heteroskedasticity and Autocorrelation
Week - 14	Applications

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
Toplam (%)		0