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- School of Science
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School of Engineering
- Undergraduate major in Mechanical Engineering
- Undergraduate major in Systems and Control Engineering
- Undergraduate major in Electrical and Electronic Engineering
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- Undergraduate major in Industrial Engineering and Economics
- Common courses
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
- School of Environment and Society
- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
-
School of Environment and Society
- Department of Architecture and Building Engineering
- Department of Civil and Environmental Engineering
- Department of Transdisciplinary Science and Engineering
- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Teacher education courses
- Instructor(s)
- Kuriyama Naoko Hagiuda Nobuko
- Class Format
- Exercise
- Media-enhanced courses
- Day/Period(Room No.)
- Thr5-6(W9-319)
- Group
- -
- Course number
- LAT.A404
- Credits
- 1
- Academic year
- 2019
- Offered quarter
- 2Q
- Syllabus updated
- 2019/3/19
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
This is a companion exercise course of LAT.A402 in which students learn how to use R to do the multivariate analysis of educational data.
Student learning outcomes
Master how to do the multivariate analysis using R.
Keywords
Statistical package, R, ICT Problem solving,Statistical perspective, Multivariate analysis
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | Practical and/or problem-solving skills |
Class flow
We set up two classes, “Strictery and Explanation of Typical Analysis Methods” and “Review of Lectures → Overcoming Stumbles and Confirmation of Cautions → Applied Tasks”.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Regression | Regression |
| Class 2 | Factor analysis | Factor analysis |
| Class 3 | Factor analysis | Factor analysis |
| Class 4 | Cluster analysis and Classification of observations | Cluster analysis and Classification of observations |
| Class 5 | Cluster analysis and Classification of observations | Cluster analysis and Classification of observations |
| Class 6 | Comprehensive analysis exercise | Comprehensive analysis exercise |
| Class 7 | Comprehensive analysis exercise | Comprehensive analysis exercise |
| Class 8 | review test and presentation | total review |
Textbook(s)
Handouts will be provided.
Reference books, course materials, etc.
Introduced when necessary.
Assessment criteria and methods
attendance: 20%
assignment: 40%
review test: 40%
Related courses
- LAT.A403 ： Practices for Psychological and Educational Measurement A
Prerequisites (i.e., required knowledge, skills, courses, etc.)
Equivalent knowledge of LAT.A403
