2021 Methods of Analysis for Socioeconomic and Environmental Data

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Academic unit or major
Graduate major in Global Engineering for Development, Environment and Society
Instructor(s)
Abe Naoya  Sakamoto Yoshie 
Course component(s)
Lecture    (ZOOM)
Day/Period(Room No.)
Fri7-8()  
Group
-
Course number
GEG.S412
Credits
1
Academic year
2021
Offered quarter
1Q
Syllabus updated
2021/3/19
Lecture notes updated
-
Language used
English
Access Index

Course description and aims

This course aims to equip the enrolled students to have the basic understandings of the socioeconomic and environmental data as well as the skills to conduct several analytical methods by themselves. The course will be combined with online lectures and the hands-on exercise by using R.

Student learning outcomes

Enrolled students will have:
1) the basic knowledge of the meaning, significance and structure of basic socioeconomic and environmental data
2) the skills to conduct basic quantitative analysis by utilizing the data above and,
3) the skills to present the results of those analysis.

Keywords

Socioeconomic data, environmental data, quantitative analysis, multivariate analysis, R

Competencies that will be developed

Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

This course consists of both lectures and hands-on excises.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Meaning, significance and basics structure of socioeconomic and environmental data Brief assignment
Class 2 Socioeconomic and environmental comparison among countries and visualization of their states and changes. Brief assignment
Class 3 Understanding the relationship between socioeconomic and environmental aspects Brief assignment
Class 4 Characteristics of our decisions for socioeconomic and environmental activities, which are often discrete, not continuous. Brief assignment
Class 5 Merits and demerits of the focus on the “average” among performing individuals or organizations. A method of analysis with the focus on the “best” for seeking better decision. Brief assignment
Class 6 Understanding a main feature of a subject, which has multiple dimensions. Brief assignment
Class 7 Summary of this class and consultation Final report

Out-of-Class Study Time (Preparation and Review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.

Textbook(s)

None (necessary materials will be distributed.)

Reference books, course materials, etc.

None (necessary materials will be distributed.)

Assessment criteria and methods

- Individual final report: about 60%
- Brief report for each session: about 40% in total sessions

Related courses

  • GEG.E413 : Geospatial data analysis for environment studies
  • GEG.E501 : Environmental Impact Assessment

Prerequisites (i.e., required knowledge, skills, courses, etc.)

Students should have basic understanding and experience in statistics and multivariate analysis.

Other

Enrolled students need to prepare a laptop PC or Mac (either windows or mac) and to be ready to use R. If you have difficulty for the preparation, contact the instructor in advance.  For the installation of R, please check the following site.
https://www.r-project.org/

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