2024 Faculty Courses School of Environment and Society Department of Transdisciplinary Science and Engineering Graduate major in Global Engineering for Development, Environment and Society
Basic Behaviormetrics: Theory and Methods
- Academic unit or major
- Graduate major in Global Engineering for Development, Environment and Society
- Instructor(s)
- Fumitake Takahashi
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 3-4 Tue / 3-4 Fri
- Class
- -
- Course Code
- GEG.T413
- Number of credits
- 200
- Course offered
- 2024
- Offered quarter
- 2Q
- Syllabus updated
- Mar 14, 2025
- Language
- English
Syllabus
Course overview and goals
Human behaviors depend on many factors like interests, perceptions, and conditions. Although marketing surveys have focused on perceptions and sensibility of consumers, sensibility is also important in various engineering applications. In order to incorporate human senses into engineering, we need to quantify it as the first step. In this course, students will learn basic methods how to measure human sensibility and preferences.
Course description and aims
This course gives you introductory lectures on basic behaviormetrics, in particular focusing on human preferences. Basic concepts of human perceptions, models of preferences, and statistical approaches to quantify human sensibility and preferences will be explained.
The purpose of this course is to provide you with an understanding of basic logic and methods to quantify human sensibility and preference. In addition, this course aims to let you understand preconditions for quantification methods and their limitations. You are expected to acquire the skills to apply quantification methods to real cases.
Keywords
Human perception, preference, quantification, statistical approach
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
15 lectures consists of 3 themes; qualitative analysis, quantitative analysis, and pairwise comparison. After a set of lectures for each theme, you will have proficiency tests to evaluate your understanding. In some lectures, you will calculate statistically using spreadsheet software (EXCEL or others).
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Human perception and sensibility: Concept and applications | You can explain the concept of human sense measurement. |
| Class 2 | Qualitative analysis I: The difference between two means | You can detect statistical significance of the difference between two groups. |
| Class 3 | Qualitative analysis II: The difference between two means | You can detect statistical significance of the difference between two means. |
| Class 4 | Proficiency test I: Qualitative analysis | Acquire the skill to detect statistical significance of two group data. |
| Class 5 | Quantitative analysis I: Scale conversion model and psychological stimulus intensity function | You can explain scale conversion using psychological stimulus intensity function. |
| Class 6 | Quantitative analysis II: Pairwise comparison I – Thurstone’s approach | You can quantify psychological stimulus intensity by pairwise comparison method with Thurstone's law of comparative judgement. |
| Class 7 | Quantitative analysis III: Coefficient of consistency | You can evaluate consistency of quenstionee's answers. |
| Class 8 | Quantitative analysis IV: Coefficient of agreement | You can evaluate agreement among quenstionees. |
| Class 9 | Proficiency test II: Pairwise comparison I | You can understand pairwise comparison method sufficiently. |
| Class 10 | Quantitative analysis V: Analysis of Variance | You can detect statistical significance of the difference among three or more than three means. |
| Class 11 | Proficiency test III: Analysis of Variance | You can understand ANOVA sufficiently. |
| Class 12 | Quantitative analysis V: Pairwise comparison II – Scheffe’s approach | You can quantify psychological stimulus intensity by pairwise comparison method with Scheffe's approach. |
| Class 13 | Proficiency test IV: Pairwise comparison II – Scheffe’s approach | You can sufficiently understand pairwise comparison method with Scheffe's approach. |
| Class 14 | Case study: Trash bin design and psychological preference | You can analyze psychological preference data for trash bin designs. |
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)
None required.
Reference books, course materials, etc.
Lecture materials are provided during class. Because you will calculate statistics, you need to take a laptop computer with spreadsheet software (EXCEL or others).
Evaluation methods and criteria
Your score will be evaluated based on only final test score.
Related courses
- ZUS.M201 ： Probability Theory and Statistics
- MEC.B231 ： Probability Theory and Statistics
Prerequisites
None required. However, it is recommended to complete statistics class before this class.
Other
Because you will calculate statistics, you need to take a laptop computer with spreadsheet software (EXCEL or others).
If course registration exceeds 45, the registration may be limited.