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日本大学ロゴ

社会学応用研究

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令和３年度以降入学者 社会学応用研究
教員名 濱本真一
単位数    2 課程 前期課程 開講区分 文理学部
科目群 社会学専攻
学期 前期 履修区分 選択必修
授業形態 対面授業
授業の形態 All classes will be held on site. Some homework may be changed to homework depending on the participant's schedule.
授業概要 Applied Statistics in Sociology of Education
In this class, we will study a introduction to applied statistics using R computing. This year we aim to understand the essence of Hierarchical Linear Modeling (HLM), which is also known as Multilevel Modeling, Fixed/Random effect modeling, or Mixed effect Modeling. The basis of statistics is essential in any science, including sociology. To better understand statistics, it is necessary to observe the behavior of the data through demonstrations. The statistical open-source software R is widely used because of its flexibility for data analysis. This class aims to understand both the basic theories of statistics and the actual analytical methods using them.
授業のねらい・到達目標 Expected Learing Goals
Through this course, participants are expected to be able to:
(1) read and well understand textbook written in English,
(2) understand the basic concepts of Multilevel modeling,
(3) understand how theories of sociology are tested empirically,
(4) systematically collect and review previous researces about your study, and
(5) establish and explain multilevel modeling in sociology.
授業の形式 演習
授業の方法 The style of course
Participants are required to:
  • summarize and explain the contents of the textbook to the class, and

  • demonstrate the analytical methods of their assigned section using R.


We will promote understanding through in-class discussion.
All class schedules and shared materials will be managed through the Class Website. Participants will be invited to the portal site.
You need to get the Notion personal account. We reccomend to use them in academic plan with your NU-Apps address.
履修条件 Recquired
  • Undergraduate-level programming and English are required.

  • Who can correctly answer the questions in Class website.

  • Cross-enrollment is permitted. Highly motivated graduate students are welcome.

  • Students must attend the first class, as the instructor will be assigned.
授業計画
1 Introduction: Activating R and Notion

【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （2時間）
2 Linear models
(chap. 1)
【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （2時間）
3 Multilevel Data Structure
(chap. 2)
【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （2時間）
4 2 Level Model
(chap. 3)
【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （2時間）
5 3 Level Model
(chap. 4)
【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （2時間）
6 Reviewing

【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （2時間）
7 Longitudinal Data Analysis
(chap. 5)
【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （2時間）
8 Data Visualization in Multilevel Models
(chap. 6)
【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （2時間）
9 Generalized Liniear Model
(chap. 7)
【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （2時間）
10 Multilevel Generalized Liniear Model
(chap. 8)
【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （2時間）
11 Reviewing

【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （2時間）
12 Bayesian Multilevel Modeling
(chap. 9)
【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （2時間）
13 Multilevel Latent Variables 1
(chap. 10)
【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （4時間）
14 Multilevel Latent Variables 2
(chap. 10)
【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself. （4時間）
15 Additional Modeling with Multilevel data
(chap. 11)
【事前学習】Prepare the resume / Clearify the unclear point of the article （4時間）
【事後学習】Define the learning you need and work on it yourself.
その他
教科書 W. Holmes Finch, Jocelyn E. Bolin, Multilevel Modeling Using R, Chapman & Hall, 2024
参考書 Julian J. Faraway, Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models:Texts in Statistical Science, Chapman & Hall, 2016, 2 edition
John Verzani, Using R for Introductory Statistics:The R Series, Chapman & Hall, 2014, 2 edition
Joop J. Hox, Multilevel Analysis: Techniques and Applications:Quantitative Methodology Series, Routeredge, 2010, 2 edition
------------------------
Notice
Other quality papers or books will be presented in the class.
成績評価の方法及び基準 授業参画度:Shared materials. (100%)
Participants MUST read a lot of English articles. Translating English papers and understanding them are essentially two different things. Using AI-based automatic translation is not prohibited, but it means that it may not hold much academic value for you. AI tools may outperform humans when it comes to translating English papers. If you do not have the willingness to go beyond that level, we do not recommend taking this course.
オフィスアワー Time: Tuesday 14:40-16:10
Location: My Laboratory (Main building 3rd floor)
備考 All classes will be held in Japanese
If you are interested in the Sociology of Education, I recommend you take the undergraduate class that provides the fundamental sociology of education.
Participate actively in the discussion. Not speaking anything in the classroom is equal to not being there.

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