[Summary of the course] The course teaches fundamentals of data analysis useful in chemistry-related research fields such as chemical engineering, applied chemistry, polymer engineering with practices. The course also teaches operation of data analysis on computer based on understanding of mathematical background of data analysis with practices on computer.
[Aim of the course] The aim of the course is for students to understand expression methods of data; definitions of statistics; regression analysis; Chi-squared test; discrete probability distribution; continuous probability distribution; probability density distribution; Fourier series. The course also aims that students can operate data analysis on computer by getting ability to write computer program.
By completing this course, students will be able to:
(1) Explain statistics of data
(2) Conduct regression analysis and explain the relation between two variables
(3) Conduct reliability test
(4) Explain discrete probability distribution, continuous probability distribution and probability density distribution
(5) Conduct Fourier series expansion of periodic function and explain characteristics of the function by interpreting Fourier coefficients
(6)Write and use program for data analysis on computer
data analysis, statistics, probability, reliability test, Fourier series
✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | ✔ Practical and/or problem-solving skills |
For each topic, its fundamentals are taught, and subsequently, programming exercises are conducted on computer to enhance understanding and programming skills.
Course schedule | Required learning | |
---|---|---|
Class 1 | Fundamentals of programming (input/output, variable, data type, operator, conditional branch, comparison operator, loop) | To code input/output, variable, data type, operator, conditional branch, comparison operator, loop. |
Class 2 | Solution of equation, linear equation system, numerical integration | To code for solving equation/linear equation system and for conducting numerical integration. |
Class 3 | Fundamentals of finite difference method and approximate solution of differential equation | To explain finite difference method and approximate solution of differential equation. |
Class 4 | Analysis of transport phenomena by finite difference method | To analyze transport phenomena by finite difference method. |
Class 5 | Methods of statistics | To explain methods of statistics. |
Class 6 | Discrete probability distribution and continuous probability distribution | To explain discrete probability distribution and continuous probability distribution. |
Class 7 | Fundamentals of random variation data analysis, Fourier transform and spectral analysis | To explain Fourier series. |
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.
Text book specified by the instructor.
Unspecified.
Learning achievement is evaluated by:
exercise in class: 20%
Final exam: 80%
No prerequisites.