2016 Basic Behaviormetrics: Theory and Methods

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Academic unit or major
Graduate major in Global Engineering for Development, Environment and Society
Takahashi Fumitake 
Course component(s)
Day/Period(Room No.)
Tue5-6(G512)  Fri5-6(G512)  
Course number
Academic year
Offered quarter
Syllabus updated
Lecture notes updated
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Course description and aims

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.

Student learning outcomes

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.


Human perception, preference, quantification, statistical approach

Competencies that will be developed

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

  Course schedule Required learning
Class 1 Human perception and sensibility: Concept and applications You can explain the concept of human sense measurement.
Class 2 Qualitative analysis I: One-way analysis of variance You can explain one-way analysis of variance.
Class 3 Qualitative analysis II: Multiple comparison You can explain multiple comparison for variance analysis.
Class 4 Proficiency test I: Qualitative analysis Acquire the skill to analyze psychological preference data qualitatively.
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: Least-square method and maximum-likelihood method You can explain least-square method and maximum-likelihood method.
Class 7 Proficiency test II: Quantitative analysis You get the skill to analyze psychological preference data quantitatively.
Class 8 Quantitative analysis III: Pairwise comparison You can explain pairwise comparison.
Class 9 Quantitative analysis IV: Coefficient of consistency You can explain coefficient of consistency for pairwise comparison method.
Class 10 Quantitative analysis V: Coefficient of agreement You can explain coefficient of agreement for pairwise comparison method.
Class 11 Proficiency test III: Pairwise comparison You get the skill to analyze pairwise comparison data and its reliability.
Class 12 Quantitative analysis VI: Factor analysis You can explain factor analysis.
Class 13 Experimental design method You can explain experimental design method.
Class 14 Case study: Trash bin design and psychological preference You can analyze psychological preference data for trash bin designs.
Class 15 Proficiency test IV: Experimental design and analysis for psychological preference survey You can explain psychological preference survey and analyze its data.


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).

Assessment criteria and methods

Your score will be evaluated based on your understanding of basic logic and methods to quantify human sensibility and preference. Score of final test and 4 times proficiency tests will be weighted 40% and 60% to calculate your credit score.

Related courses

  • ZUS.M201 : Probability Theory and Statistics
  • MEC.B231 : Probability Theory and Statistics

Prerequisites (i.e., required knowledge, skills, courses, etc.)

None required. However, it is recommended to complete statistics class before this class.


Because you will calculate statistics, you need to take a laptop computer with spreadsheet software (EXCEL or others).

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