M362003Sociology (Seminars)
| Numbering Code | G-LET30 7M362 SJ45 | Year/Term | 2022 ・ Year-round | |
|---|---|---|---|---|
| Number of Credits | 4 | Course Type | Seminar | |
| Target Year | Target Student | |||
| Language | Japanese | Day/Period | Fri.4 | |
| Instructor name | TAROUMARU HIROSHI (Graduate School of Letters Professor) | |||
| Outline and Purpose of the Course | Students will acquire practical knowledge and skills for hands-on planning, design, conduct, analysis, and aggregation of social surveys. In addition, students will gain an understanding of the analytical methods using measurement models common to multivariate analysis, based on the fundamentals of mathematical statistics. We will focus on analyzing data and interpreting results using a computer. | |||
| Course Goals | Students will acquire the ability to analyze data and expand their knowledge regarding the range of techniques used for data analysis. | |||
| Schedule and Contents |
First semester 1. Research methodology and research ethics 2. Research planning and design (1) 3. Research planning and design (2) 4. Composing hypotheses 5. Constructing scale 6. Sampling or selection of target fields (1) 7. Sampling or selection of target fields (2) 8. Preparing questionnaires (1) 9. Preparing questionnaires (2) 10. Investigation 11. Organizing survey data (coding, data cleaning, etc.) (1) 12. Organizing survey data (coding, data cleaning, etc.) (2) 13. Creating graphs, hypothesis verification (1) 14. Greating graphs, hypothesis verification (2) 15. Creating a report Second semester 1. Reviewing regression analysis 2. Nonlinear models (logarithmic conversion, introduction of square terms) 3. Examination of interaction effect 4. Selecting a model (AIC, BIC, F-test) 5. Model diagnostics (residual plot, VIF) 6. Binary logistic regression analysis (1) 7. Binary logistic regression analysis (2) 8. Maximum likelihood estimation method and likelihood ratio test (1) 9. Maximum likelihood estimation method and likelihood ratio test (2) 10. Multinomial logistic regression analysis (1) 11. Multinomial logistic regression analysis (2) 12. Ordered logistic regression analysis (1) 13. Ordered logistic regression analysis (2) 14. How to summarize results of analysis and using graphs (1) 15. How to summarize results of analysis and using graphs (2) |
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| Evaluation Methods and Policy | Attendance (25 percent), homework (25 percent), and reports (50 percent) | |||
| Course Requirements | Students must be qualified social researchers or posses equivalent knowledge. | |||
| Study outside of Class (preparation and review) | Emphasis will be on preparation. Homework will be assigned. | |||
| Textbooks | Textbooks/References | Introduced in class. | ||
| References, etc. | Introduced in class. | |||
