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- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
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School of Environment and Society
- Department of Architecture and Building Engineering
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- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Teacher education courses
- Instructor(s)
- Matsuda Toshiki Kuriyama Naoko
- Class Format
- Exercise (Blended)
- Media-enhanced courses
- Day/Period(Room No.)
- Thr5-6()
- Group
- -
- Course number
- LAT.A403
- Credits
- 1
- Academic year
- 2022
- Offered quarter
- 1Q
- Syllabus updated
- 2022/4/1
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
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Course description and aims
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.
Student learning outcomes
Students wiil be able to perform data analysis, such as calculation of basic statistics, statistical tests, ANOVA, multiple comparison, and multiple regression analysis, by using Excel or R Commander.
Keywords
Statistical data analysis, Excel, R Commander, Problem-solving, Statistical Ways of Viewing and Thinking
Competencies that will be developed
| ✔ 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”. Please check the web-page of Matsuda Lab. to confirm the schedule.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Introduction（An E-mail from m-domain address is required until 12:00 on April 13th.） | Install R Commander |
| Class 2 | Calculation of basic statistics and Histogram | Calculation of basic statistics and Histogram |
| Class 3 | Calculation of basic statistics and Histogram | Calculation of basic statistics and Histogram |
| Class 4 | Cross tabulation, Scatter plot and Correlation | Cross tabulation, Scatter plot and Correlation |
| Class 5 | Cross tabulation, Scatter plot and Correlation | Cross tabulation, Scatter plot and Correlation |
| Class 6 | ANOVA | ANOVA |
| Class 7 | ANOVA | ANOVA |
| Class 8 | End-term test and Regression Analysis | Review test and regression |
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.
Assessment criteria and methods
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.A404 ： Practices for Psychological and Educational Measurement B
Prerequisites (i.e., required knowledge, skills, courses, etc.)
Students who do not take "Introduction to Psychological and Educational Measurement" together cannot take this course
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.
