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- Liberal arts and basic science courses
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- School of Science
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- School of Life Science and Technology
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School of Environment and Society
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- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Teacher education courses
- Instructor(s)
- Hagiuda Nobuko
- Class Format
- Lecture (Livestream)
- Media-enhanced courses
- Day/Period(Room No.)
- Thr5-6()
- Group
- -
- Course number
- LAT.A401
- Credits
- 1
- Academic year
- 2022
- Offered quarter
- 1-2Q
- Syllabus updated
- 2022/4/1
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
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Course description and aims
- Themes of course are statistical methods and mutivariable analysis methods as well as the warp and woof model of problem-solving for stastical analysis.
- This course is integrally managed with "Practices for Psychological and Educational Measurement A & B."
Student learning outcomes
The goal of this course is to master the basic techniques of statistics often used in the areas of education and psychology.
Keywords
Introductory and intermediate statistics
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | Practical and/or problem-solving skills |
Class flow
The lessons of this course and exercises of "Practices for Psychological and Educational Measurement" are provided as paired lectures every two weeks on a class day.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Basic Statistics and statistical tests (An E-mail from m-domain address is required until 12:00 on April 14th.) | Review after exercises by the gaming instructional material |
| Class 2 | Correlation and cross tabulation | Review after exercises by the gaming instructional material |
| Class 3 | Analysis of variance | Review after exercises by the gaming instructional material |
| Class 4 | Regression analysis | Review after exercises by the gaming instructional material |
| Class 5 | Principal component analysis and factor analysis | Review after exercises by the gaming instructional material |
| Class 6 | Cluster analysis | Review after exercises by the gaming instructional material |
| Class 7 | Comprehensive analysis | Review after exercises by the gaming instructional material |
| Class 8 | End term test and review | Review of the lessons |
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 for " Introduction to Psychological and Educational Measurement A & B."
(Additional information will be introduced when necessary.)
Assessment criteria and methods
Homework Exercises and End term examination (both 1Q and 2Q)
Related courses
- LAT.A403 ： Practices for Psychological and Educational Measurement A
- LAT.A402 ： Introduction to Psychological and Educational Measurement B
- LAT.A404 ： Practices for Psychological and Educational Measurement B
Prerequisites (i.e., required knowledge, skills, courses, etc.)
"Practices for Psychological and Educational Measurement A" is required to be taken 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
Office hours by appointment.
