PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
ISY 642	DATA ANALYSIS IN ECONOMETRICS AND STATISTICS SOFTWARE	3 + 0	1st Semester	10

COURSE DESCRIPTION

Course Level	Doctorate Degree
Course Type	Elective
Course Objective	Some econometric and statistical softwares (SPSS, STATA, E-Views, Excel) will be introduced so that Ph.D. students will be able to conduct modelling and testing financial data.
Course Content	Provisions is given concrete examples of concepts via example data sets, a data set econometric problems encountered can be overcome by what means knowledge gained
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

1	knows the statistical and econometric concepts
2	knows properties of financial data
3	recognize the econometric problems of financial data
4	use one packet program at least
5	to explain data analysis can be reached at the end of the process of finding with financial arguments

COURSE'S CONTRIBUTION TO PROGRAM

	PO 01	PO 02	PO 03	PO 04	PO 05	PO 06	PO 07
LO 001	5	5	5	2	5	3	3
LO 002	3	5	5	2	5	3	3
LO 003	3	5	5	2	5	3	3
LO 004	5	5	5	2	5	3	3
LO 005	3	5	5	2	5	3	3
Sub Total	19	25	25	10	25	15	15
Contribution	4	5	5	2	5	3	3

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	5	70
Assignments	4	15	60
Mid-terms	1	25	25
Final examination	1	30	30
Presentation / Seminar Preparation	3	11	33
Total Work Load ECTS Credit of the Course			260 10

COURSE DETAILS

Select Year

	Course Term	No	Instructors
Details	2020-2021 Fall	1	DÜNDAR KÖK

Course Details

Course Code	Course Title	L+P Hour	Course Code	Language Of Instruction	Course Semester
ISY 642	DATA ANALYSIS IN ECONOMETRICS AND STATISTICS SOFTWARE	3 + 0	1	Turkish	2020-2021 Fall

Course Coordinator	E-Mail	Phone Number	Course Location	Attendance
Prof. Dr. DÜNDAR KÖK	dkok@pau.edu.tr		İİBF A0116	%

Goals		Some econometric and statistical softwares (SPSS, STATA, E-Views, Excel) will be introduced so that Ph.D. students will be able to conduct modelling and testing financial data.
Content		Provisions is given concrete examples of concepts via example data sets, a data set econometric problems encountered can be overcome by what means knowledge gained

Topics

Weeks	Topics
1	Basic Concepts of Statistics and Econometrics
2	Basic Concepts of Statistics and Econometrics
3	Distinguishing Features of Financial Data
4	Financial Data Analysis Methodology in Statistical Programs
5	Financial Data Analysis Methodology in Statistical Programs
6	Financial Data Analysis Methodology in Statistical Programs
7	Financial Data Analysis Methodology in Statistical Programs
8	Midterm Exam
9	Case study
10	Case study
11	Case study
12	Case study
13	Case study
14	Case study

Materials

Materials are not specified.

Resources

Resources	Resources Language
2. Philip Hans Franses and Dick Van Dijk, Non-Linear Time Series Models in Empirical Finance, Cambridge University Press, 2nd Edition, USA, 2003	English
1. Chris Brooks, Intraductory Econometrics For Finance, 2nd Edition, Cambridge Unv.Press, 2008.	English
2. Philip Hans Franses and Dick Van Dijk, Non-Linear Time Series Models in Empirical Finance, Cambridge University Press, 2nd Edition, USA, 2003	English
1. Chris Brooks, Intraductory Econometrics For Finance, 2nd Edition, Cambridge Unv.Press, 2008.	English
2. Philip Hans Franses and Dick Van Dijk, Non-Linear Time Series Models in Empirical Finance, Cambridge University Press, 2nd Edition, USA, 2003	English
1. Chris Brooks, Intraductory Econometrics For Finance, 2nd Edition, Cambridge Unv.Press, 2008.	English

Course Assessment

Assesment Methods	Percentage (%)	Assesment Methods Title
Final Exam	50	Final Exam
Midterm Exam	50	Midterm Exam

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

Prospective Student