学部・大学院区分
Undergraduate / Graduate
法学部
時間割コード
Registration Code
0380032
科目区分
Course Category
専門科目
Specialized Courses
科目名 【日本語】
Course Title
エコノメトリックスI(E)
科目名 【英語】
Course Title
Introductory EconometricsⅠ(E)
担当教員 【日本語】
Instructor
岡島 広子 ○
担当教員 【英語】
Instructor
OKAJIMA Hiroko ○
単位数
Credits
2
開講期・開講時間帯
Term / Day / Period
秋 火曜日 3時限
Fall Tue 3
対象学年
Year
1年
1
授業形態
Course style
講義
Lecture


授業の目的 【日本語】
Goals of the Course(JPN)
授業の目的 【英語】
Goals of the Course
Students will learn summary statistics necessary to extract information from data. Various tools to visualize data are presented using Excel and R (a programming language for statistical analysis). In addition, students will learn simple regression models.
到達目標 【日本語】
Objectives of the Course(JPN)
At the end of the course, all students will be able to:
1. Demonstrate an understanding of summary statistics.
2. Create a data set using Excel.
3. Estimate and visualize summary statistics using R.
4. Run simple regressions and interpret the results.
到達目標 【英語】
Objectives of the Course
授業の内容や構成
Course Content / Plan
This course is composed of lectures, in-class activities (exercises using Excel and R, discussions, and quizzes), homework assignments, and a term paper. The topics covered in this course are:
1. Introduction & installing R
2. Sorting out data in Excel: basic tools
3. Sorting out data in Excel: advanced tools
4. Basic operations in R: working directory, saving scripts
5. Basic operations in R: reading data files
6. Basic operations in R: summary function
7. Basic operations in R: review
8. RStudio
9. Boxplots, hinges, and quartiles in R
10. Histogram in R
11. Scatter plots and correlation coefficients in R
12. Regression
13. Regression in R: part 1
14. Regression in R: part 2
15. Review
履修条件・関連する科目
Course Prerequisites and Related Courses
None
成績評価の方法と基準
Course Evaluation Method and Criteria
1. Term paper (50%): Detailed instructions will be distributed around the 7th week. Students' papers will be graded using a grading rubric provided in the instructions. Late submission will be accepted with a 10% penalty per day (24-hour period).
2. Assignment (20%): There will be about 5 homework assignments. Each homework has a due date. Late submission will be accepted with a penalty of a 10% deduction per day (24-hour period).
3. Class participation (15%): There will be various in-class activities (e.g., exercises, discussions, and quizzes). Students who actively participate in these activities will receive points for class participation.
4. Class attendance (15%): If a student anticipates an excused absence, he/she must notify the instructor in person or by emails to be excused. A proof (e.g., a doctor's note) is not required for the first absence but is required for the second and subsequent absences to be excused.
教科書・テキスト
Textbook
There is no textbook required for this course.
参考書
Reference Book
課外学習等(授業時間外学習の指示)
Study Load(Self-directed Learning Outside Course Hours)
Students are expected to review course materials taught in each class. Previewing of course materials is not required.
注意事項
Notice for Students
Students must bring their computers to every class to use R. Smartphones and tablets cannot be used for this purpose. Instructions for the installment of R will be provided during the first class meeting.
授業開講形態等
Lecture format, etc.
If the educational activity level is 1 or less, face-to-face lessons will be held in principle. However, for students who do not wish to take face-to-face lessons, it will be conduct "face-to-face / ICT-based remote classes (two-way or simultaneous on-demand)". ICT-based remote classes will be conduct by NUCT etc. When conducting an on-demand lesson, students should use the NUCT feature "Messages" to ask teachers questions and exchange opinions about lessons between students.
* If the class format changes after registration (after this notification), we will notify you on the NUCT class site.
遠隔授業(オンデマンド型)で行う場合の追加措置
Additional measures for remote class (on-demand class)