2019 Experimental Methods of Earth and Planetary Sciences (safety and data analysis)

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Academic unit or major
Undergraduate major in Earth and Planetary Sciences
Yokoyama Tetsuya  Ueno Yuichiro  Ohta Kenji  Haba Makiko  Sato Bunei  Nakajima Junichi  Hirano Teruyuki 
Class Format
Media-enhanced courses
Day/Period(Room No.)
Course number
Academic year
Offered quarter
Syllabus updated
Lecture notes updated
Language used
Access Index

Course description and aims

The instructor lectures on the importance and regulations of safety management in the university with special reference to the department class. Lectures on data analysis provide several useful statistical methods for Earth and Planetary Sciences.

Student learning outcomes

Every student learns safety management necessary for studying at the university. Students learn fundamental knowledge and applications of the statistical treatment of scientific data in data analysis.


Safety management, Waste material, Data analysis, Statistical treatment

Competencies that will be developed

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

Class flow

The instructor will explain many examples of safety management and data analysis, and each student can apply the knowledge to their studies at university.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Safety management: Introduction Understanding objectives of the class.
Class 2 Safety management: How to treat waste materials Learning the university regulations of waste materials.
Class 3 Safety management: Risk in experimental study Learn safety management for field works, chemistry experiments, high pressure and temperatures, high voltage, etc.
Class 4 Data analysis: Normal distribution Fundamental theory of normal distribution and its application to several examples.
Class 5 Data analysis: Errors Fundamental theory of error analysis and propagation of errors
Class 6 Data analysis: The least square method Fundamental theory and application of the least square fitting.
Class 7 Data analysis: Principal component analysis Fundamental theory and application of the principal component analysis.
Class 8 Data analysis: Polynomial approximation and model selection Fundamental theory and application of the polynomial approximation and selection of the optimal order.


No specific textbook.

Reference books, course materials, etc.

Materials necessary for the class will be given.

Assessment criteria and methods

The score is determined from several reports on subjects related to the lecture.

Related courses

  • EPS.L205 : Laboratory in Earth and Planetary Sciences (field geology)
  • EPS.L202 : Laboratory in Earth and Planetary Sciences (petrology)
  • EPS.L203 : Laboratory in Earth and Planetary Sciences (geochemistry)
  • EPS.L204 : Laboratory in Earth and Planetary Sciences (geophysical measurements)
  • EPS.B201 : Mathematics for Physics A (EPS course)
  • EPS.B210 : Mathematics for Physics B (EPS course)
  • EPS.A204 : Introduction to Earth and Planetary Physics

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

No requirements.


This lecture is for undergraduate students in Department of the Earth and Planetary Sciences.

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