Data Science ｜ Syllabus data

授業科目名

Data Science

学年

1Grade

単位数

2.00Credits

実務経験の有無

開講クォーター

semester not specified

担当教員

Komatsu Goro

授業形態

授業で主に使用する言語

English

授業方法区分

開講キャンパス

Kioicho Campus

授業の到達目標及びテーマ

This course provides advanced statistical methods for Causal Inference and Econometrics analysis.

Students will also have hands-on experiences on R programming languages, to apply those methodologies to real world data.

No programming skills are required. We also welcome those who are interested in programming and data scientists.

*Students must bring their own laptop computers for the in-class programming exercises.

*It is highly recommended that students have already taken credits in Statistics offered by GSIA.
*It is also strongly recommended to register for this class if you plan to use Regression Analysis for your master thesis.

授業の概要

Course Title: Data Science

Class Format: Lecture

Content:
The course consists of two parts. In the first part, students have hands-on experiences in R programming languages with the instructor. Students then apply those programming skills to Econometric analysis in the second part of the class.

Keyword:
Data Science, Econometrics, Experimental Studies, Randomized Controlled Trials (RCT), Observational Studies, Causal Inference, Regression, Programing, Data Visualization, R

Week 1—Introduction to R
01 Introduction to R (1) (QSS Ch.1)
02 Introduction to R (2) (QSS Ch.1 Exercises)

Week 2—Causality
03 Experimental Studies (QSS 2.1-2.2)
04 Observational Studies (QSS 2.3-2.6)

Week 3—Measurement, Prediction
05 Measurement (QSS Ch.3)
06 Prediction (QSS Ch.4)

Week 4—Simple Regression Analysis
07 Simple Regression Analysis (1) (Wooldridge, Ch.2)
08 Simple Regression Analysis (2) (Wooldridge, Ch.3)

Week 5—Multiple Regression Analysis
09 Multiple Regression Analysis (1) (Wooldridge, Ch.4,5,6)
10 Multiple Regression Analysis (2) (Wooldridge, Ch.7,8,9)

Week 6—Causal Inference and Program Evaluation
11 Panel Data, Difference-in-Differences (Wooldridge, Ch.14,15)
12 Instrumental Variables, RMarkdown (Wooldridge, Ch.13)

Week 7—Presentation
13 Final-Project Presentation

授業計画

1回

01 Introduction to R (1) (QSS Ch.1)

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