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2023 Faculty Courses School of Environment and Society Undergraduate major in Civil and Environmental Engineering

Basic Mathematics for System Science

Academic unit or major
Undergraduate major in Civil and Environmental Engineering
Instructor(s)
Nobuhiro Chijiwa / Yasunori Muromachi
Class Format
Lecture/Exercise (Face-to-face)
Media-enhanced courses
-
Day of week/Period
(Classrooms)
5-6 Tue (MI1-107(M114)) / 5-6 Fri (MI1-107(M114))
Class
-
Course Code
CVE.M202
Number of credits
110
Course offered
2023
Offered quarter
2Q
Syllabus updated
Jul 8, 2025
Language
Japanese

Syllabus

Course overview and goals

This course is composed of lectures and exercises on basics of (1) eigenvalue problems, (2) systems of ordinary differential equations and (3) statistical methodologies for civil engineering.
Students are expected to be capable of understanding the basics and applying them to simple problems for civil engineering.

Course description and aims

Students are expected to be capable of understanding the basics of (1) eigenvalue problems, (2) systems of ordinary differential equations and (3) statistical methodologies and applying them to simple problems for civil engineering.

Keywords

Eigenvalue problems, Systems of ordinary differential equations, Statistics, Probability

Competencies

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

Class flow

Lecture and exercises

Course schedule/Objectives

Course schedule Objectives
Class 1 Data and Basic Statistics (YM) Understanding the concept of data and basic statistics
Class 2 Concept of Random Variable (YM) Understanding the concept of random variable
Class 3 Regression Analysis (YM) Understanding and practising regression analysis
Class 4 Statistical Estimation (YM) Understanding and practising statistical estimation
Class 5 Statistical Hypothesis Testing (YM) Understanding and practising statistical hypothesis testing
Class 6 Experimental Design, Analysis of Variance, and Development of Statistical Approach (YM) Understanding and practising experimental design, analysis of variance, and development of statistical approach
Class 7 Summary of statistical approach (YM) Understanding statistical approach
Class 8 Basics of matrices and vectors (NC) Understanding basics of matrices and vectors
Class 9 Eigenvalues and eigenvectors (NC) Understanding eigenvalues and eigenvectors
Class 10 Basics of ordinary differential equations (NC) Understanding basics of ordinary differential equations
Class 11 Homogeneous ordinary differential equations (NC) To enable to solve homogeneous ordinary differential equations
Class 12 Non-homogeneous ordinary differential equations (NC) To enable to solve nonhomogeneous ordinary differential equations
Class 13 Systems of ordinary differential equations (NC) To enable to solve systems of ordinary differential equations
Class 14 Summary of eigenvalue problems and systems of ordinary differential equations (NC) Understanding eigenvalue problems and systems of ordinary differential equations

Study advice (preparation and review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.

Textbook(s)

First half: Handouts will be provided by the instructor
Last half: Handouts will be provided by the instructor

Reference books, course materials, etc.

First half: None
Last half: Erwin Kreyszig, Advanced Engineering Mathematics 10th Edition, John Wiley & Sons (ISBN: 978-0-470-64613-7)

Evaluation methods and criteria

First half: Assignments (40%) and exam (60%)
Latter half: Assignments (20%) and exam (80%)

Related courses

  • LAS.M102 : Linear Algebra I / Recitation
  • LAS.M106 : Linear Algebra II
  • LAS.M108 : Linear Algebra Recitation II
  • CVE.M201 : Basic Mathematics for Physical Science

Prerequisites

None

Other

None