Print

2017　Basic Behaviormetrics: Theory and Methods

Font size  SML

Register update notification mail Add to favorite lecture list
Academic unit or major
Graduate major in Global Engineering for Development, Environment and Society
Instructor(s)
Takahashi Fumitake 
Class Format
Lecture     
Media-enhanced courses
Day/Period(Room No.)
Tue3-4(G512)  Fri3-4(G512)  
Group
-
Course number
GEG.T413
Credits
2
Academic year
2017
Offered quarter
2Q
Syllabus updated
2017/5/30
Lecture notes updated
-
Language used
English
Access Index

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.

Keywords

Human perception, preference, quantification, statistical approach

Competencies that will be developed

✔ 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/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: 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.
Class 15 Proficiency test V: Practice and analysis for psychological preference survey You can explain psychological preference survey and analyze its data.

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).

Assessment criteria and methods

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

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).

Page Top