Numbering Code		Year/Term	2022 ・ First semester
Number of Credits	2	Course Type	Lecture
Target Year		Target Student
Language	English	Day/Period	Thu.2
Instructor name	ADACHI TAKANORI (Graduate School of Management Associate Professor)
Outline and Purpose of the Course	This course introduces students to the basics of data analysis, with emphasis on applications for business, economic, and policy issues. Participating students are expected to think about connections between what they learn in class and the real-world problems and situations that they are interested in.
Course Goals	The students are expected to learn a variety of techniques for data analysis. In particular, (1) what kind of dataset is available/should be created, (2) what kind of method should be used, and (3) how to provide sensible analysis for their research question. Additionally, it is also desirable to take care of better presentation of their empirical results.
Schedule and Contents	1. Explanatory Data Analysis 2. Comparison and Correlation 3. Generalizing from Data 4. Testing Hypotheses 5. Simple Regression 6. Generalizing Results of a Regression 7. Multiple Linear Regression 8. Modeling Probabilities 9. Regression with Time Series Data 10. Forecasting from Time Series Data 11. A Framework for Causal Analysis 12. Difference-in-Differences 13. Methods for Panel Data 14. Appropriate Control Groups for Panel Data 15. Review
Evaluation Methods and Policy	Based on the final exam (closed-book; 70-80%) and some other interim work such as assignments (20-30%).
Course Requirements	Basic knowledge of statistics is required. RStudio (freely downloadable) must be installed on your computer.
Study outside of Class (preparation and review)	Participating students are expected to regularly review class slides after each lecture.
Textbooks	Textbooks/References	Data Analysis for Business, Economics, and Policy, Bekes, G.; Kezki, G., (Cambridgre University Press, 2021), ISBN:9781108716208
Related URL	Please check this site regularly.