Course title
A00070002
Applied Analysis

 SAWA Takekazu
Course description
In this course, students link quality management and quality engineering and learn how to collect experimental data and scientific predictive analysis methods.
Purpose of class
Learn data sensing methods and statistical analysis methods.
Goals and objectives
  1. Students can identify features of the data and perform appropriate sensing.
  2. Students can use different statistical-based analysis methods to find information.
  3. Students will understand quality engineering and be able to effectively evaluate problems and propose solutions.
Relationship between 'Goals and Objectives' and 'Course Outcomes'

 Intermediate test Term-end exam Total.
1. 15% 15% 30%
2. 15% 15% 30%
3. 20% 20% 40%
Total. 50% 50% -
Evaluation method and criteria
The result is determined by 50% on the mid-term test and 50% on the final test, with a total score of 60% or higher.
The passing criterion is defined as the ability to correctly select a method and perform calculations to arrive at a solution to a given problem.
Language
Japanese
Class schedule

 Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1. Overview of Statistical Methods
　The Need for Data Science
　What is data?
　Reliability Theory 		Preparation and review using reference materials 190minutes
2. Quality Control
　Various Methods
　Parameter Design 		Preparation and review using reference materials 190minutes
3. Statistics
　Population and Sample
　Data Processing
　Stochastic variables and their distributions 		Preparation and review using reference materials 190minutes
4. Statistical Analysis Techniques (1)
　Regression analysis
　Principal Component Analysis
　Process analysis using data 		Preparation and review using reference materials 190minutes
5. Statistical Analysis Methods (2)
　Process analysis using data 		Preparation and review using reference materials 190minutes
6. Production Engineering and Quality Control (1)
　Simple Tests of Correlation Coefficients
　Tests and Estimation of Total Values 		Preparation and review using reference materials 190minutes
7. Mid-term test and review of previous tests Preparation and review using reference materials 190minutes
8. Production Engineering and Quality Control (2)
　Process Control
　Production Process Index
　Standardization and Internal Standards 		Preparation and review using reference materials 190minutes
9. Application of Statistical Methods to Quality Control
Control Charts
Process capability index
Hypothesis testing
　Other Methods 		Preparation and review using reference materials 190minutes
10. Design of Experiments
Introduction to Design of Experiments
Multiple allocation and variance
Orthogonal Table Experiments 		Preparation and review using reference materials 190minutes
11. Quality Engineering (1)
Procedure for calculating signal-to-noise ratio
Planning of experiments 		Preparation and review using reference materials 190minutes
12. Quality Engineering (2)
Application Examples 		Preparation and review using reference materials 190minutes
13. Summary of the lecture, review of the whole lecture Preparation and review using reference materials 190minutes
14. Final Exam and Critique Preparation and review using reference materials 190minutes
Total. - - 2660minutes
Feedback on exams, assignments, etc.
ways of feedback specific contents about "Other"
Feedback in the class
Textbooks and reference materials
Use the text in the distribution folder.
Prerequisites
It is desirable for students to have taken Basic Analysis and Exercises in Analysis.
Office hours and How to contact professors for questions
  • After the lecture. However, it is advisable to inform the students in advance of the visit.
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Non-social and professional independence development course
Active-learning course
N/A
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicable
Applicable Guidance on how to tackle problem solving by utilizing practical experience.
Education related SDGs:the Sustainable Development Goals
  • 4.QUALITY EDUCATION
  • 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
Last modified : Thu Mar 06 10:30:02 JST 2025