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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
- Undergraduate major in Information and Communications Engineering
- 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
- Graduate major in Chemical Science and Engineering
- Instructor(s)
- Zettsu Koji Kasai Yasko Yoshida Naohiro
- Class Format
- Lecture
- Media-enhanced courses
- Day/Period(Room No.)
- Thr1-2(G115)
- Group
- -
- Course number
- CAP.E421
- Credits
- 1
- Academic year
- 2017
- Offered quarter
- 3Q
- Syllabus updated
- 2017/3/17
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
This course focuses on how to handle experimental data and analyse them. Statistical theories as well as probability theory required for data analysis will be lectured.
Student learning outcomes
By the end of this course, students will be able to treat experimetal data statistically and to analyse logically.
Keywords
statistical processing, error analysis, probability theory, data analysis
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | ✔ Practical and/or problem-solving skills |
Class flow
Individual topics will be lectured.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Introduction to scientific data analysis | Introduction to scientific data analysis |
| Class 2 | Generation of errors and its analysis | Generation of errors and its analysis |
| Class 3 | Fundamentals of probability theory | Fundamentals of probability theory |
| Class 4 | Fundamentals of statistical theory I | Fundamentals of statistical theory I |
| Class 5 | Fundamentals of statistical theory II | Fundamentals of statistical theory II |
| Class 6 | Analysis of experimental data I | Analysis of experimental data I |
| Class 7 | Analysis of experimental data I | Analysis of experimental data I |
| Class 8 | Term-end examination and the review. | Term-end examination and the review. |
Textbook(s)
unfixed
Reference books, course materials, etc.
unfixed
Assessment criteria and methods
unfixed
Related courses
- CAP.E422 ： Presentation Practice
- CAP.E521 ： Scientific Ethics
Prerequisites (i.e., required knowledge, skills, courses, etc.)
none
