PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
EKNM 401	TIME SERIES ANAYSIS - I	3 + 0	7th Semester	5

COURSE DESCRIPTION

Course Level	Bachelor's Degree
Course Type	Compulsory
Course Objective	The aim of this lecture is of introduce to time series econometrics.
Course Content	ARIMA, Diagnostic Checking, Model Selection, ARMA, ARIMA, Forecasting
Prerequisites	No the prerequisite of lesson.
Corequisite	EKNM 301 ECONOMETRICS - I
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

1	: Understanding the properties of time series
2	Application of time series econometrics methods
3	ARIMA models
4	Forecasting

COURSE'S CONTRIBUTION TO PROGRAM

	PO 01	PO 02	PO 03	PO 04	PO 05	PO 06	PO 07	PO 08	PO 09	PO 10	PO 11	PO 12
LO 001	5	5	5	5	5	5	5	5	5	5	5	5
LO 002	4	4	5	5	5	5	1	5	5	5	5	5
LO 003	5	5	5	5	5	5	1	4	5	5	5	5
LO 004	3	4	5	5	5	5	2	5	5	5	5	5
Sub Total	17	18	20	20	20	20	9	19	20	20	20	20
Contribution	4	5	5	5	5	5	2	5	5	5	5	5

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Hours for off-the-classroom study (Pre-study, practice)	14	3	42
Assignments	1	10	10
Mid-terms	1	16	16
Final examination	1	20	20
Total Work Load ECTS Credit of the Course			130 5

COURSE DETAILS

Select Year

	Course Term	No	Instructors
Details	2023-2024 Fall	1	SİNEM GÜLER KANGALLI UYAR

Course Details

Course Code	Course Title	L+P Hour	Course Code	Language Of Instruction	Course Semester
EKNM 401	TIME SERIES ANAYSIS - I	3 + 0	1	Turkish	2023-2024 Fall

Course Coordinator	E-Mail	Phone Number	Course Location	Attendance
Assoc. Prof. Dr. SİNEM GÜLER KANGALLI UYAR	skangalli@pau.edu.tr		İİBF C0203	%60

Goals		The aim of this lecture is of introduce to time series econometrics.
Content		ARIMA, Diagnostic Checking, Model Selection, ARMA, ARIMA, Forecasting

Topics

Weeks	Topics
1	Time series components
2	Stationarity
3	Non-stationarity process
4	Stationarity process
5	Auto regressive models
6	Moving average models
7	Midterm exam
8	ARMA models
9	ARIMA models
10	Unit root tests
11	Dickey-Fuller and Augmented Dickey Fuller tests
12	Fi tests
13	Application
14	Final exam

Materials

Materials are not specified.

Resources

Resources	Resources Language
Applied econometric time series (Walter Enders)	English

Course Assessment

Assesment Methods	Percentage (%)	Assesment Methods Title
Final Exam	60	Final Exam
Midterm Exam	40	Midterm Exam

L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes

Prospective Student