| Academic Year |
2024Year |
School/Graduate School |
Graduate School of Advanced Science and Engineering (Master's Course) Division of Advanced Science and Engineering Transdisciplinary Science and Engineering Program |
| Lecture Code |
WSQN2101 |
Subject Classification |
Specialized Education |
| Subject Name |
Management and Conservation of Ecosystems |
Subject Name
（Katakana） |
|
Subject Name in
English |
Management and Conservation of Ecosystems |
| Instructor |
HOSAKA TETSURO,HISANO MASUMI |
Instructor
(Katakana) |
ホサカ テツロウ,ヒサノ マスミ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
1st-Year, First Semester, 1Term |
| Days, Periods, and Classrooms |
(1T) Tues1-4：IDEC 204 |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
|
- Class style: Face to Face, Online
- (If online) Bb9, Teams, Zoom or something else
|
| Credits |
2.0 |
Class Hours/Week |
|
Language of Instruction |
E
:
English |
| Course Level |
5
:
Graduate Basic
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
03
:
Natural Environment |
| Eligible Students |
Master student |
| Keywords |
|
| 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 |
Undestanding of statistical analyses is essential for sustainable ecosystem management. This lecture aims to provide basic knowledges and skills of statistical analyses required for analyzing changes of natural ecosystems and relationship between environmental factors and ecosystem responses. Students will also practice the analyses with a statistical analysis software, R, and sample dataset so that they can conduct the analyses by themselves. |
| Class Schedule |
lesson1 Basic backgrounds of statistical analyses (1)
lesson2 Basic backgrounds of statistical analyses (2)
lesson3 Introduction to R and non-parametric tests (1)
lesson4 Introduction to R and non-parametric tests (2)
lesson5 Non-parametric tests (3)
lesson6 Non-parametric tests (4)
lesson7 Analysis of Variance (1)
lesson8 Analysis of Variance (2)
lesson9 Analysis of Variance (3)
lesson10 Correlation and regression analysis (1)
lesson11 Correlation and regression analysis (2)
lesson12 Generalized Linear Models (1)
lesson13 Generalized Linear Models (2)
lesson14 Generalized Linear Mixed Models (1)
lesson15 Generalized Linear Mixed Models (2) |
Text/Reference
Books,etc. |
Handout will be provided |
PC or AV used in
Class,etc. |
|
| (More Details) |
Handout, Power point |
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
Some references will be introduced |
| Requirements |
Please bring your own laptop |
| Grading Method |
Evaluation will be based on scores of review test after each class |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
|
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. |