Undergraduate
Faculty of Economic and Administrative Sciences
International Trade (English)
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International Trade (English) Main Page / Program Curriculum / DATA ANALYSIS AND IN SOCIAL SCIENCES

DATA ANALYSIS AND IN SOCIAL SCIENCES

Course CodeSemester Course Name LE/RC/LA Course Type Language of Instruction ECTS
ITR0063 DATA ANALYSIS AND IN SOCIAL SCIENCES 2/0/0 DE English 4
Course Goals
 Specifically, this course aims to develop

·                     the analytical skills to deal with the data in social sciences.

·         the ability to use the tools of statistics to explain, analyze and resolve economic issues, and evaluate policy decisions;

the habit of reading critically, from a variety of sources, to gain information about the policies at the national and international levels and interpret the data.

Prerequisite(s) NA
Corequisite(s) NA
Special Requisite(s) NA
Instructor(s) Assoc. Prof. Nebile Korucu Gümüşoğlu
Course Assistant(s)
Schedule Tuesday 09:00-10:50
Office Hour(s) WEdnesday, 11:00-13:00
Teaching Methods and Techniques -Lectures, Online materials, Open courses, IMF, Central Bank, OECD, Eurostat web sites.
Principle Sources -
Social Research Methods, W. Lawrence Neuman, Pearson. Business Research Methods, Zikmund, Babin, Carr and Griffin, 9th edition, Cengage Publishing.
Data Analysis for the Social Sciences, Douglas Bors, SAGE Publishing.
Other Sources -
Course Schedules
Week Contents Learning Methods
1. Week What is data? Introduction to Data Types Presentations and discussions
2. Week Data Types (qualitative, quantitative) Presentations and discussions
3. Week Determination of appropriate data Presentations and discussions
4. Week Using databases Presentations and discussions
5. Week Analysis methods used in social sciences Presentations and discussions
6. Week Data analysis by using SPSS Presentations and discussions
7. Week Data analysis by using SPSS Presentations and discussions
8. Week Midterm -
9. Week Midterm -
10. Week Data analysis by using R and Python Presentations and discussions
11. Week Data analysis by using R and Python Presentations and discussions
12. Week Presentations Presentations and discussions
13. Week Presentations Presentations and discussions
14. Week Presentations Presentations and discussions
15. Week Final Exam
16. Week Final Exam
17. Week Final Exam
Assessments
Evaluation tools Quantity Weight(%)
Quizzes 2 10
Project(s) 1 40
Final Exam 1 50


Program Outcomes
PO-1Comprehends both theoretical and applied subjects in international trade at the advanced level, and uses his/her knowledge when necessary.
PO-2Analyses basic concepts and data related to International Trade and Economics by scientific methods, interprets those with analytically, and evaluates those with regard to economic issues.
PO-3Express his/her thoughts, comments and evaluations related to International Trade discipline both in written and oral forms.
PO-4Defines current problems, and proposes solutions which are supported by evidence and research based quantitative and qualitative data.
PO-5Inspects how public and private sector enterprises engaged in trade activities operates in practice, and evaluates the continuities and the dynamism in these sectors.
PO-6Defines and tracks local, regional (such as European Union or Middle East) and global issues from the point of political economics, and relates these issues to each other.
PO-7Possesses sufficient knowledge in other disciplines related to International Trade (such as Economics, Finance, International Business and Law), and reports this information.
PO-8Follows publications and research in International Trade, Globalisation and Financial Systems in the English language, and communicates with his/her colleagues internationally.
PO-9Uses a second language (Russian, Chinese, etc.) at the intermediate level.
PO-10Possesses ethical principles and scientific values in collection, interpretation and release of data.
Learning Outcomes
LO-1can separate data types.
LO-2can determine which data type should be used.
LO-3can withdraw the required data from the most appropriate database.
LO-4can apply appropriate data analysis methods
LO-5can interpret the analyzes and future implications
Course Assessment Matrix:
Program Outcomes - Learning Outcomes Matrix
 PO 1PO 2PO 3PO 4PO 5PO 6PO 7PO 8PO 9PO 10
LO 1
LO 2
LO 3
LO 4
LO 5