GISDepartment of Global and Interdisciplinary Studies
PRI100ZA（情報学基礎 / Principles of informatics 100）StatisticsStatistics
荻原 祐二Yuji OGIHARA
授業コードなどClass code etc
| 学部・研究科Faculty/Graduate school | GISDepartment of Global and Interdisciplinary Studies |
| 添付ファイル名Attached documents | |
| 年度Year | 2022 |
| 授業コードClass code | A6042 |
| 旧授業コードPrevious Class code | |
| 旧科目名Previous Class title | |
| 開講時期Term | 秋学期授業/Fall |
| 曜日・時限Day/Period | 木3/Thu.3 |
| 科目種別Class Type | |
| キャンパスCampus | 市ヶ谷 / Ichigaya |
| 教室名称Classroom name | 各学部・研究科等の時間割等で確認 |
| 配当年次Grade | 1～4 |
| 単位数Credit(s) | 2 |
| 備考（履修条件等）Notes | |
| 他学部公開科目Open Program | |
| 他学部公開（履修条件等）Open Program (Notes) | |
| グローバル・オープン科目Global Open Program | |
| 成績優秀者の他学部科目履修制度対象Interdepartmental class taking system for Academic Achievers | ○ |
| 成績優秀者の他学部科目履修（履修条件等）Interdepartmental class taking system for Academic Achievers (Notes) | 制度ウェブサイトの3．科目別の注意事項 (1) GIS主催科目の履修上の注意を参照すること。 |
| 実務経験のある教員による授業科目Class taught by instructors with practical experience | |
| SDGsCPSDGs CP | |
| アーバンデザインCPUrban Design CP | |
| ダイバーシティCPDiversity CP | |
| 未来教室CPLearning for the Future CP | |
| カーボンニュートラルCPCarbon Neutral CP | |
| 千代田コンソ単位互換提供（他大学向け）Chiyoda Campus Consortium | |
| 旧科目との重複履修Duplicate Subjects Taken Under Previous Class Title | |
| カテゴリー（2024年度以降入学者）Category (commenced 2024 onwards) | |
| カテゴリー（2020～2023年度入学者）Category (commenced 2020-2023) | |
| カテゴリー（2016～2019年度入学者）Category (commenced 2016-2019) |
すべて開くShow all
すべて閉じるHide All
授業の概要と目的（何を学ぶか）Outline and objectives
In this course, students learn basic concepts and skills of statistical methods and data analysis.
到達目標Goal
The objective of this course is twofold. First, students learn basic concepts in statistics (e.g., mean, standard deviation, standard error, normal distribution, t-test and regression analysis). Second, practical skills for visualizing data and conducting appropriate statistical tests are introduced and students practice them using statistical software.
この授業を履修することで学部等のディプロマポリシーに示されたどの能力を習得することができるか（該当授業科目と学位授与方針に明示された学習成果との関連）Which item of the diploma policy will be obtained by taking this class?
Will be able to gain “DP 1”, “DP 2”, and “DP 4”.
授業で使用する言語Default language used in class
英語 / English
授業の進め方と方法Method(s)（学期の途中で変更になる場合には、別途提示します。 /If the Method(s) is changed, we will announce the details of any changes. ）
This is an introductory course on statistical methods and data analysis. It explains the basic ideas behind statistical testing and covers various statistical methods for survey and experimental data. Each class combines a lecture with hands-on exercises (free statistical software are used). In addition, an assignment is given after every class. At the beginning of class, feedback for the previous class is given using some comments from submitted assignments. Students are encouraged to ask questions and to be actively involved in the class.
アクティブラーニング（グループディスカッション、ディベート等）の実施Active learning in class (Group discussion, Debate.etc.)
あり / Yes
フィールドワーク（学外での実習等）の実施Fieldwork in class
なし / No
授業計画Schedule
授業形態/methods of teaching：対面/face to face
※各回の授業形態は予定です。教員の指示に従ってください。
1[オンライン/online]：Introduction
Overview of course and requirements
2[対面/face to face]：Descriptive Statistics (1)
Introducing basic descriptive statistics (e.g., mean, median, mode)
3[対面/face to face]：Descriptive Statistics (2)
Introducing basic descriptive statistics (e.g., standard deviation, variance, standard error)
4[対面/face to face]：Correlation
The relationship between two variables
5[対面/face to face]：Population and Sample
Random sampling and distribution of population
6[対面/face to face]：Probability Distribution
Probability distribution and Z-score
7[対面/face to face]：Hypothesis Testing and Statistical Tests
Testing your hypothesis using statistical tests and sampling distribution
8[対面/face to face]：Regression Analysis (1)
Single regression analysis
9[対面/face to face]：Regression Analysis (2)
Multiple regression analysis
10[対面/face to face]：T-test (1)
Testing if the difference is significant
11[対面/face to face]：T-test (2)
Related and unrelated t-tests
12[対面/face to face]：Analysis of Variance
Introducing ANOVA
13[対面/face to face]：Categorical Data Analysis
Introducing categorical data analysis
14[対面/face to face]：Summary & In-class Exam
Overall summary and in-class exam
授業時間外の学習（準備学習・復習・宿題等）Work to be done outside of class (preparation, etc.)
Students are encouraged to review their lecture notes and handouts after each class. Preparatory study and review time for this class are 2 hours each.
テキスト（教科書）Textbooks
No textbook will be used. Handouts and reading materials will be provided by lecturer.
参考書References
References will be introduced in class.
成績評価の方法と基準Grading criteria
Students will be evaluated on the basis of assignments given in each class (50%) and in-class exam (50%). No credit will be given to students with more than two unexcused absences.
学生の意見等からの気づきChanges following student comments
None.
その他の重要事項Others
This course is strongly recommended for students interested in various disciplines in social sciences.
Those who take and pass this course may be given priority in the enrollment of some of the psychology courses.
Prerequisite
None.