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.
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 understand and to present the results of those analyses.
Socioeconomic data, environmental data, quantitative analysis, multivariate analysis, R
✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | ✔ Practical and/or problem-solving skills |
This course consists of both lectures and hands-on excises.
Course schedule | Required learning | |
---|---|---|
Class 1 | Introduction to this course: meaning, significance and basics structure of socioeconomic and environmental data、Basic commands of R | Brief assignment |
Class 2 | Measurement of the intensity of relationship between socioeconomic and environmental variables (correlation coefficients and scales) | Brief assignment |
Class 3 | Analysis of a relationship between socioeconomic and environmental aspects (regression analysis for quantitative variables) | Brief assignment |
Class 4 | Discreteness of our decisions for socioeconomic and environmental activities (discrete choice model) | Brief assignment |
Class 5 | Discreteness of our decisions for socioeconomic and environmental activities (multi-nominal discrete choice model, continued) | Brief assignment |
Class 6 | Dimension reduction of socioeconomic and environmental data (principal component analysis and clustering analysis)Measurement of performance efficiency of a decision-making unit when there are multiple inputs and outputs (basics of data envelopment analysis) | Brief assignment |
Class 7 | Measurement of performance efficiency of a decision-making unit when there are multiple inputs and outputs (basics of data envelopment analysis) | Final report |
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.
None (necessary materials will be distributed.)
None (necessary materials will be distributed.)
- Individual final report: about 60%
- Brief report for each session: about 40% in total sessions
Students should have basic understanding and experience in statistics and multivariate analysis. There could be registration quota if the number of the registered students exceed more than 40.
Content of each session may change and be adjusted, depending on the progress of lectures. Enrolled students need to prepare a laptop PC or Mac (either windows or mac) and to be ready to use R. For the installation of R, please check the following site and install it.
https://www.r-project.org/