2022 Faculty Courses Liberal arts and basic science courses Teacher education courses
Practices for Psychological and Educational Measurement B
- Academic unit or major
- Teacher education courses
- Instructor(s)
- Toshiki Matsuda / Naoko Kuriyama
- Class Format
- Exercise (Blended)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 5-6 Thu
- Class
- -
- Course Code
- LAT.A404
- Number of credits
- 010
- Course offered
- 2022
- Offered quarter
- 2Q
- Syllabus updated
- Jul 10, 2025
- Language
- Japanese
Syllabus
Course overview and goals
The course will focus on teaching statistical methods and the Warp and Woof model to do the statistical analysis of either psychological or educational data.
Course description and aims
Students wiil be able to perform data analysis, such as principle componet analysis, factor analysis, and cluster analysis, by using Excel or R Commander.
Students will be able to perform comprehensive data analysis by using of statsical methods systematically.
Keywords
Statistical package, R Commander, ICT Problem-solving, Statistical Ways of Viewing and Thinking, Multivariate analysis
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
We set up two classes, “Strictery and Explanation of Typical Analysis Methods” and “Review of Lectures → Overcoming Stumbles and Confirmation of Cautions → Applied Tasks”.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Regression analysis | Regression |
| Class 2 | Principle componet analysis andFactor analysis | Factor analysis |
| Class 3 | Principle componet analysis and Factor analysis | Factor analysis |
| Class 4 | Cluster analysis | Cluster analysis |
| Class 5 | Cluster analysis、Comprehensive analysis | Cluster analysis、Comprehensive analysis |
| Class 6 | Comprehensive analysis exercise | Comprehensive analysis exercise |
| Class 7 | Comprehensive analysis exercise | Comprehensive analysis exercise |
| Class 8 | Final test and presentation | Report |
Study advice (preparation and review)
Textbook(s)
Matsuda, T. and Hagiuda, N. (Eds.) (2021) Introduction to data science for problem-solving, Jikkyo Syuppan.
Reference books, course materials, etc.
E-learning materials will be provided.
Evaluation methods and criteria
Achievement levels of e-learning materials, pre-and-post exercises for each lesson, end-term test
Related courses
- LAT.A401 ： Introduction to Psychological and Educational Measurement
- LAT.A403 ： Practices for Psychological and Educational Measurement A
Prerequisites
Students are required to earn the credit for "Practices for Psychological and Educational Measurement A" and take "Introduction to Psychological and Educational Measurement" concurrently.
Contact information (e-mail and phone) Notice : Please replace from ”[at]” to ”@”(half-width character).
stat-ask[at]et.hum.titech.ac.jp
Office hours
By appointment.