| Academic Year |
2024Year |
School/Graduate School |
School of Science |
| Lecture Code |
HX334200 |
Subject Classification |
Specialized Education |
| Subject Name |
物理学特別講義（実践データ解析法Ａ（宇宙）） |
Subject Name
（Katakana） |
ブツリガクトクベツコウギ（ジッセンデータカイセキホウエー（ウチュウ）） |
Subject Name in
English |
Special Lectures in Physics(Practical Data Analysis A (Space Physics)) |
| Instructor |
TAKAHASHI HIROMITSU |
Instructor
(Katakana) |
タカハシ ヒロミツ |
| Campus |
|
Semester/Term |
2nd-Year, First Semester, 2Term |
| Days, Periods, and Classrooms |
(2T) Inte |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
|
| |
| Credits |
1.0 |
Class Hours/Week |
|
Language of Instruction |
J
:
Japanese |
| Course Level |
3
:
Undergraduate High-Intermediate
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
06
:
Physics |
| Eligible Students |
2-4 grade students |
| Keywords |
Practical data analysis, Astrophysics, Astronomy, Parameter estimate |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Class Objectives
/Class Outline |
Learn the basics of practical data analysis method (estimation of physical quantities) using astrophysical data observed by satellites.
・ Learn the concepts necessary for analyzing measurement / observation data in physics.
・ Obtain basic knowledge to explain widely used data analysis methods. |
| Class Schedule |
・ Detector operation
・ Analog data, digital data
・ Data calibration and physical quantity
-
・ Astronomical observation data
・ Image, light curve, energy spectrum
・ Error, background
-
・ Data analysis (estimation of physical quantities)
・ Model function
・ Normal distribution and least-squares method
・ Poisson distribution and maximum-likelihood method
・ Bayesian inference |
Text/Reference
Books,etc. |
Copies of ppt silds will be distributed as a reference. |
PC or AV used in
Class,etc. |
|
| (More Details) |
PC |
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
Ask questions to the lecturers when you do not understand contents of the lecture and procedures of analysis. Students practically analyze experimental data by using your own PC. It is important to develop your skill by analyzing data repeatedly via the practical learning. |
| Requirements |
|
| Grading Method |
Evaluate the grade via submitted reports of data analysis. |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
This class is currently planned in August. Please check Momiji for the latest information. |
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |