TE507 Computer Use in Economic Researches

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code TE507
Name Computer Use in Economic Researches
Term 2022-2023 Academic Year
Term Spring
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Dr. Öğr. Üyesi CAHİT GÜNGÖR
Course Instructor
1


Course Goal / Objective

To introduce students updated softwares to use for summarising and interpreting the data obtained from the studies in the area of agricultural economics.

Course Content

Data sources in Agricultural economics, data analysis techniques, computer softwares for data analysis

Course Precondition

Resources

Notes



Course Learning Outcomes

Order Course Learning Outcomes
LO01 is able to analyze data and interpret the results obtained from the studies in the area of agricultural economics.
LO02 is able to apply statistical analyses techniques using softwares..
LO03 is able to apply optimization and artificial intelligence techniques in agricultural economics..
LO04 is able to analyze data and interpret the results obtained from the studies in the area of agricultural economics
LO05 is able to apply statistical analyses techniques using softwares.
LO06 is able to apply optimization and artificial intelligence techniques in agricultural economics.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Able to further develop and deepen knowledge acquired based on the undergradute level proficiencies in the fields of farm management and agricultural policy 2
PLO02 Bilgi - Kuramsal, Olgusal Able to comprehend interactions among related disciplines and field of agricultural economics
PLO03 Bilgi - Kuramsal, Olgusal Able to use theoretical and practical knowledge of agricultural economics in their specialization area
PLO04 Bilgi - Kuramsal, Olgusal Able to prepare reports on developments in national economy and agricultural sector; able to critically evaluate historical and actual developments in agriculture and economy; able to observe and interpret economics related publications
PLO05 Bilgi - Kuramsal, Olgusal Able to use software widely used in agricultural economics
PLO06 Bilgi - Kuramsal, Olgusal Able to combine data of actual developments with his knowledge, data and findings obtained in various disciplines and interpret them while supporting them with qualitative and quantitative data and also forming new knowledge through synthesis
PLO07 Bilgi - Kuramsal, Olgusal Ability to take the lead in multidisciplinary teams and work in teams
PLO08 Beceriler - Bilişsel, Uygulamalı Able to critically evaluate specialized knowledge and abilities acquired in agricultural economics and direct his/her own learning process
PLO09 Beceriler - Bilişsel, Uygulamalı Constantly adapt himself to new scientific developments
PLO10 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Able to use acquired and digested agricultural economics knowledge in multidisciplinary studies, able to explain them, to transfer them to others, able to examine conclusions critically
PLO11 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Able to transfer research results using verbal, written and visual tools 1
PLO12 Yetkinlikler - Öğrenme Yetkinliği Able to collect data according to scientific methods in order to solve economic problems, able to supervise and interprete data collected while taking into consideration social, scientific and ethical values
PLO13 Yetkinlikler - Öğrenme Yetkinliği Able to develop analytical approaches in order to solve complicated problems that cannot be forecast beforehand in applications of agricultural economics and policy; able to design research process; able to produce solutions by taking on responsibility and to evaluate and justify solutions


Week Plan

Week Topic Preparation Methods
1 Data sources in Agricultural analysis and softwares Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
2 Data sort, filter, simple and conditional calculations Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
3 Clustering data and preparing summary tables Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
4 Connecting tables, preparing new tables and making calculations Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
5 Connecting tables, preparing new tables and making calculations (continue) Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
6 Graphic types and preparing graphics Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
7 Graphic types and preparing graphics (continue) Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
8 Mid-Term Exam Exam Ölçme Yöntemleri:
Yazılı Sınav, Sözlü Sınav
9 Functions are using in economic analysis Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
10 Statistical analysis Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
11 Optimization models and solving the models. Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
12 Optimization models and solving the models (continue) Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
13 Artificial intelligence techniques and solving the models. Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
14 Artificial intelligence techniques and solving the models (continue) Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
15 Artificial intelligence techniques and solving the models (continue) Lecture notes and recommended resources for the relevant sections Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
16 Term Exams Exam Ölçme Yöntemleri:
Yazılı Sınav, Sözlü Sınav
17 Term Exams Exam Ölçme Yöntemleri:
Yazılı Sınav, Sözlü Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 14.11.2022 10:33