In this course the student will learn how to identify the data structures used in management, sales, marketing, production management, finance, and accounting, how to collect data from primary sources, hot to organize the collected data, how to describe, and how to analyse them according to the aim of the reaearch. at the end of the course the students will be able to analyse the problems which could arise in any business analytical, to offer the needed solutions, to forecast the future of the business and to determine the causality relatios in the businesses. Besides they will be able to use SPSS, MPlus and Eviews.
Prerequisite(s)
Course Code Course Name…
Corequisite(s)
Course Code Course Name…
Special Requisite(s)
The minimum qualifications that are expected from the students who want to attend the course.(Examples: Foreign language level, attendance, known theoretical pre-qualifications, etc.)
Instructor(s)
Professor Evren Ayrancı
Course Assistant(s)
Schedule
Tuesday, 18:00-21:00 (Ataköy, 3B 08-10)
Office Hour(s)
Ataköy, Tuesday, 18.00-21.00 3B 08-10
Teaching Methods and Techniques
-Lectures, application sampling.
Principle Sources
· Maxwell, S. E., & Delaney, H. D. (2004). Designing experiments and analyzing data: A model comparison perspective (2nd ed.). Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers.
· Fernandes, Marcelo. (2009). Statistics for Business and Economics.
· Statistics for Business & Economics, Revised 13th Edition by David R. Anderson; Dennis J. Sweeney; Thomas A. Williams and Publisher Cengage Learning.
· SPSS, Eviews, Mplus.
Other Sources
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Course Schedules
Week
Contents
Learning Methods
1. Week
The definitons of research and data analyses. The selection of suitable technique to analyse the data
Lecture
2. Week
Descriptive statistics
Lecture
3. Week
Hypothesis Testing, parametric techniques
Lecture
4. Week
Hypothesis Testing, parametric techniques
Lecture
5. Week
Nonparametric techniques
Lecture
6. Week
Relationship analysis
Lecture
7. Week
Relationship analysis
Lecture
8. Week
Midterm
Exam
9. Week
Multivariate analysis techniques
Lecture
10. Week
Multivariate analysis techniques
Lecture
11. Week
SPSS Applications
Application
12. Week
SPSS Applications
Application
13. Week
Eviews Applications
Application
14. Week
Mplus Applications
Application
15. Week
Final Exams
Exam
16. Week
17. Week
Assessments
Evaluation tools
Quantity
Weight(%)
Midterm(s)
1
40
Final Exam
1
60
Program Outcomes
PO-1
Extend and deepen the international economics and finance knowledge acquired at the level of expertise.
PO-2
Be able to use the knowledge gained in the field of International Economics and Finance theoretically and practically.
PO-3
Evaluate the information on International Economics and Finance from a critical perspective and study independently.
PO-4
Understand and examine the interaction between different disciplines and fields related to International Economics and Finance.
PO-5
Have sufficient social responsibility and awareness about social needs and gain the experience and competence to organize activities that may affect social dynamics when necessary.
PO-6
Gain skills in model development, technical analysis and policy making in the field of economics and finance.
PO-7
Understand and evaluate any problem in the field of International Economics and Finance independently, generate solutions to these problems.
PO-8
Analyze the problems related to the field of International Economics and Finance analytically, propose economic and financial policies suitable for the solution of the problems.
PO-9
Adapt the theoretical knowledge to the professional business career.
PO-10
Develop original approaches and take responsibility in critical situations encountered in the fields of International Economics and Finance.
PO-11
In the process of collecting, interpreting and announcing the data related to the field of International Economics and Finance, be able to supervise and transfer them by considering social, rational, scientific and ethical values.
Learning Outcomes
LO-1
The students will be able to collect the data, to prepare the data to be analysed, and to analyze the data by using statistical programs.
LO-2
The students will be able to use statistical techniques to visualize and analyze the data
LO-3
The students will be able to use statisticak and quantitative techniques to provide information from the data and to forecast
LO-4
The students will gain knowledge about contemporary, theoretical and practical informations in the field of statistics.
LO-5
The students will be able to analyze the contemporary problems with statistical techniques.
