Hiroshima University Syllabus

Back to syllabus main page
Academic Year 2022Year School/Graduate School School of Economics Economics Day Course
Lecture Code G5051121 Subject Classification Specialized Education
Subject Name 計量経済学1
Subject Name
Subject Name in
Econometrics 1
ハヤカワ カズヒコ
Campus Higashi-Hiroshima Semester/Term 2nd-Year,  First Semester,  1Term
Days, Periods, and Classrooms (1T) Weds1-4:LAW/ECO B257
Lesson Style Lecture Lesson Style
(More Details)
Basically, Face-to-Face lectures are provided. However, it may switch to online lecture depending on the circumstances. 
Credits 2.0 Class Hours/Week   Language of Instruction J : Japanese
Course Level 2 : Undergraduate Low-Intermediate
Course Area(Area) 24 : Social Sciences
Course Area(Discipline) 03 : Economics
Eligible Students second year
Keywords statistical analysis of economic data, regression analysis, empirical analysis 
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Criterion referenced
Economic Analysis
(Abilities and Skills)
・The ability of developing mathematical analysis applying knowledge Economic theory, Statistics and Econometrics. 
Class Objectives
/Class Outline
Econometrics is an interdisciplinary subject composed of economics, statistics and mathematics. In this course, the statistics part is mainly considered. Specifically, this course provide a series of lectures associated with regression analysis. The goal of this course is to provide basic skills so that students can carry out simple statistical analysis.  
Class Schedule lesson1: Guidance
lesson2: What is econometrics?
lesson3: Review of statistics
lesson4: Review of statistics
lesson5:  Review of statistics
lesson6: Simple regression model
lesson7: Simple regression model
lesson8: Simple regression model
lesson9: Multiple regression model
lesson10: Multiple regression model
lesson11: Multiple regression model
lesson12: Functional form
lesson13: Dummy variable
lesson14: Dummy variable
lesson15: Summary of the course

class room report, final exam 
distribute the materials via webpage 
PC or AV used in
(More Details) slides 
Learning techniques to be incorporated  
Suggestions on
Preparation and
Every classes are interdependent, so students are required to review each class. 
Requirements Basic knowledge of statistics and mathematics 
Grading Method HW and final exam 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
Message Students who are interested in data analysis are most welcome. 
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. 
Back to syllabus main page