講義名 経済特殊講義Ⅲ(Economic StatisticsⅡ(英)) ≪◇学部≫
講義開講時期 後期
曜日・時限 火4
単位数 2

担当教員
氏名
川﨑 茂

学習目標(到達目標) Building on Economic Statistics I. students will acquire knowledge and skills of inferential statistics, multiple regression and input-output analysis, using real economic statistics.
前期Economic Statistics 1に続き,推測統計,重回帰分析,産業連関分析を用いた分析能力と英語での説明能力を修得します。
授業概要(教育目的) This course teaches basic inferential statistics, regression, input-output model, using economic statistics of Japan and other countries. Students will study how to apply them to real data.
推測統計,重回帰分析,産業連関表を中心に,日本と世界の経済統計分析の実例にを英語で学びます。
授業計画表
 
項目内容
第1回Introduction
Introduction to the course will be given. The foundation of inferential statistics and basic theories of probability will be explained.
Prior learning (2 hour): Read the material posted on EcoLink.
Subsequent learning (2 hour): Complete today's assignments.
第2回Probability and Inference (1)
Concepts of central limit theorem and normal distribution will be explained. Students will study how to apply the methods to the real cases.
Prior learning (2 hour): Read the handouts given in the previous class.
Subsequent learning (2 hour): Complete today's assignments.
第3回Probability and Inference (2)
Concepts of sampling methods, including standard error and confidence intervals, will be explained. Students will study how to apply them in real cases.
Prior learning (2 hour): Read the handouts given in the previous class.
Subsequent learning (2 hour): Complete today's assignments.
第4回Probability and Inference (3)
Concepts of hypothesis testing will be explained. Students will study the examples of application.
Prior learning (2 hour): Read the handouts given in the previous class.
Subsequent learning (2 hour): Complete today's assignments.
第5回Probability and Inference (4)
Exercises of inferential statistics will be given. Students will discuss the results.
Prior learning (2 hour): Read the handouts given in the previous class.
Subsequent learning (2 hour): Complete today's assignments.
第6回Regression Models (1)
Basic concepts of linear regression models will be explained. Students will study the sample cases.
Prior learning (2 hour): Read the handouts given in the previous class.
Subsequent learning (2 hour): Complete today's assignments.
第7回Regression Models (2)
Concepts of non-linear regression, including logarithmic and logistic regression, will be explained. Students will apply the methods to real cases.
Prior learning (2 hour): Read the handouts given in the previous class.
Subsequent learning (2 hour): Complete today's assignments.
第8回Statistical Databases (1)
Major international statistical databases will be introduced. Students will practice using them.
Prior learning (2 hour): Read the handouts given in the previous class.
Subsequent learning (2 hour): Complete today's assignments.
第9回Statistical Databases (2)
Using the databases and the statistical methods taught in the class, students will perform data analysis, and present the results.
Prior learning (2 hour): Read the handouts given in the previous class.
Subsequent learning (2 hour): Complete today's assignments.
第10回Price Indices (1)
Basic index number theories will be explained, using the real statistical series. Students will study the characteristics of various index time series data.
Prior learning (2 hour): Read the handouts given in the previous class.
Subsequent learning (2 hour): Complete today's assignments.
第11回Price Indices (2)
As an extension of price indices, concepts and methods of purchasing power parities (PPP) will be explained. Students will analyze data based on PPP.
Prior learning (2 hour): Read the handouts given in the previous class.
Subsequent learning (2 hour): Complete today's assignments.
第12回Input-Output Analysis (1)
The framework of input-output models and analysis will be explained. Students will study the theoretical background of the theories
Prior learning (2 hour): Read the handouts given in the previous class.
Subsequent learning (2 hour): Complete today's assignments.
第13回Input-Output Analysis (2)
Use of input-output tables for forecasting demands will be explained. Students will study the applied cases given in the class.
Prior learning (2 hour): Read the handouts given in the previous class.
Subsequent learning (2 hour): Complete today's assignments.
第14回Input-Output Analysis (3)
Exercises will be given. Review the two previous lessons in advance.
Prior learning (2 hour): Read the handouts given in the previous class.
Subsequent learning (2 hour): Complete today's assignments.
第15回Final Examination and Review
60 minutes for the test + 30 minutes to analyze the test. Concluding remarks will be given.
Prior learning (2 hour): Review the materials and assignments you studied in the semester, and become able to answer questions.
Subsequent learning (2 hour): Review the results of the final exam, and follow up the parts that you didn't understand well.
授業形式 Lectures will be given in the PC room. Students will work on exercises using mainly EXCEL, and present their results,
授業は,パソコン教室でエクセルを用いて進めます。講義,演習等は英語で行い,統計分析の方法や結果を英語で説明する能力を修得することを目指します。
評価方法
定期試験 レポート 小テスト 授業への
参画度
その他 合計
70% 0% 0% 30% 0% 100%
評価の特記事項 Submit the results of assignments each time. They will be considered in the assessment.
テキスト Study materials will be given in the class, and will be shared in the class public folder.
参考文献 Reference on methods: Salvatore, Reagle, Statistics and Econometrics (Second Edition), McGraw-Hill, 2011.
和文参考図書:中村隆英ほか著『経済統計入門(第2版)』東京大学出版会
オフィスアワー(授業相談) Tuesday, 16:30-18:00. Make an appointment by e-mail or at the time of the class.
事前学習の内容など,学生へのメッセージ Classroom PCs are in the Japanese version. If you need English version, bring yours to the class if possible. Preferable to have taken Economic Statistics I in the 1st Semester, but not required.
理論や手法とともに日本・世界の経済事情も学びます。統計学の事前履修は条件としません。前期「Economic Statistics I」の履修は必須としませんが,できるだけ履修してください。