2016 Advanced Data Analysis

Font size  SML

Register update notification mail Add to favorite lecture list
Academic unit or major
Graduate major in Chemical Science and Engineering
Instructor(s)
Zettsu Koji  Kasai Yasko  Yoshida Naohiro 
Course component(s)
Lecture
Day/Period(Room No.)
Thr1-2(G115)  
Group
-
Course number
CAP.E421
Credits
1
Academic year
2016
Offered quarter
3Q
Syllabus updated
2016/4/27
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

Intercultural skills Communication skills Specialist 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

Page Top