Teaching

Basic Statistics (Graduate School of Commerce, Waseda University, 2023 - )

「統計基礎」． Basic Statistics 1 (Spring), 2 (Spring), and 3 (Fall) will be offered in Japanese, and 4 (Fall) will be offered in English. The content is introductory-level statistics; the prerequisite knowledge is high school-level mathematics. 

• Main textbook: Lind, Douglas, William Marchal and Samuel Wathen (2022) Basic Statistics in Business and Economics, 10th ed, McGraw-Hill Education. / Note that students are not required to purchase it. 

• R script (GitHub)

Econometrics (Graduate School of Commerce, Waseda University, 2023 - )

「計量経済学」． The content is introductory-level econometrics; the prerequisite knowledge is introductory-level statistics and mathematics. Offered in Japanese. 

• Textbook: 鹿野繁樹 (2015) 『新しい計量経済学―データで因果関係に迫る』日本評論社．【サポートページ】 / 教科書の購入は必須ではありません．

Data Analysis Using Statistical Packages (Graduate School of Commerce/Accountancy, Waseda University, 2024 - )

「統計ソフトによるデータ解析」． The content is the implementation of statistical, econometric, and causal inference methods using R. Offered in Japanese. 

• R script (GitHub)

References for statistics and econometrics

Textbooks for beginners are marked with ★. 

• ★ Wooldridge, Jeffrey M. (2019) Introductory Econometrics: A Modern Approach, 7th ed, South-Western Pub. 【Book resources】 / An R package "wooldridge" is available that contains the datasets used in the book. A book has been published that introduces implementation in R in accordance with this book: Heiss (2020) Using R for Introductory Econometrics, 2nd ed. 

• Wooldridge, Jeffrey M. (2010) Econometric Analysis of Cross Section and Panel Data, 2nd ed, MIT Press. 【Student's Solutions Manual and Supplementary Materials】 / This is a graduate-level textbook. 

• Greene, William (2017) Econometric Analysis, 8th ed, Pearson Education.  / This is a graduate-level textbook and requires knowledge of linear algebra to understand. 

• ★ Stock, James H. and Mark W. Watson (2019) Introduction to Econometrics, 4th ed, Pearson Education. (第2版の和訳：『入門計量経済学』共立出版, 2016.)

• ★ Llaudet, Elena and Kosuke Imai (2022) Data Analysis for Social Science: A Friendly and Practical Introduction, Princeton University Press. 【Official instructor resources / Unofficial instructor materials】

• ★ Imai, Kosuke (2018) Quantitative Social Science: An Introduction, Princeton University Press. (和訳：『社会科学のためのデータ分析入門（上）・（下）』岩波書店, 2018.) / This textbook is more advanced than Llaudet and Imai (2022). 

  • cf. Imai, Kosuke. Causal Inference with Applications [with video] (Harvard)

• ★ Diez, David, Mine Cetinkaya-Rundel, and Christopher D. Barr (2019) OpenIntro Statistics, 4th ed. (和訳：『データ分析のための統計学入門』) 

• ★ Department of Statistics, University of Washington (2016) Undergraduate course: Elements of Statistical Methods / Introduction to Statistics with R. 

• ★ Angrist, Joshua D. and Jörn-Steffen Pischke (2014) Mastering 'Metrics: The Path from Cause to Effect, Princeton University Press. / This is an undergraduate-level textbook covering experimental approaches. 

• Angrist, Joshua D. and Jörn-Steffen Pischke (2009) Mostly Harmless Econometrics: An Empiricist's Companion, Princeton University Press. (和訳：『「ほとんど無害」な計量経済学―応用経済学のための実証分析ガイド』NTT出版, 2013.) / This is a graduate-level textbook covering experimental approaches. 

• Dunning, Thad (2012) Natural Experiments in the Social Sciences: A Design-Based Approach, Cambridge University Press. 

• Cunningham, Scott. Causal Inference: The Mixtape. (和訳：『因果推論入門〜ミックステープ：基礎から現代的アプローチまで』技術評論社, 2023.) / This is a textbook on causal inference using an experimental approach. 

• Huntington-Klein, Nick. The Effect: An Introduction to Research Design and Causality. 

• Goldsmith-Pinkham, Paul. Applied Empirical Methods [with video] (Yale)

• Canay, Ivan A. Econ 480-3 [with video] (Northwestern)

• Buteikis, Andrius (2020) Practical Econometrics and Data Science. / It includes both R and Python code. [2024/4 リンク切れ？] 

• ★ Çetinkaya-Rundel, Mine and Johanna Hardin (2021) Introduction to Modern Statistics, OpenIntro. 【Tutorials】

• ★ 東京大学教養学部統計学教室 (1991) 『統計学入門』東京大学出版会．

• ★ 田中隆一 (2015) 『計量経済学の第一歩―実証分析のススメ』 有斐閣．

• ★ 伊藤公一朗 (2017) 『データ分析の力―因果関係に迫る思考法』光文社．

• ★ 総務省統計局．なるほど統計学園（小・中学生向け）

• 末石直也 (2015) 『計量経済学―ミクロデータ分析へのいざない』日本評論社．

• 西山慶彦，新谷元嗣，川口大司，奥井亮 (2019) 『計量経済学』有斐閣．

  • cf. 石井俊輔: 練習問題解答とRでの再現

• 久保川達也，国友直人 (2016) 『統計学』東京大学出版会．

• 竹村彰通 (2020) 『現代数理統計学』新装改訂版，学術図書出版社．

• 永田靖 (2005) 『統計学のための数学入門30講』朝倉書店．

• ★ 九州大学 数理・データサイエンス教育研究センター．講義資料（データサイエンス概論Ⅰ＆Ⅱ，データサイエンス実践Ⅰ～Ⅳ，情報科学，他）．

• ★ 田中司朗 (2017) エレベータのブザーは鳴るか―大学生のための統計学入門，京大OCW．

• 鈴木良一 ．数理統計学（学部向けの講義資料のようです）

• 古川知志雄．統計推論再考 – 概念と技法 –．

• R

  • Wickham,  Hadley, Mine Cetinkaya-Rundel, and Garrett Grolemund (2017) R for Data Science, 2nd ed. 

  • ★ Douglas, Alex, Deon Roos, Francesca Mancini, Ana Couto, and David Lusseau (2023) An Introduction to R. 

  • Kleiber, Christian and Achim Zeileis (2008) Applied Econometrics with R, Springer. 【Slide materials, R scripts, and data】

  • Florian Oswald, Vincent Viers, Jean-Marc Robin, Pierre Villedieu, and Gustave Kenedi (Sciences Po Department of Economics) (2020) Introduction to Econometrics with R. 

  • Hanck, Christoph, Martin Arnold, Alexander Gerber, and Martin Schmelzer (2023) Introduction to Econometrics with R. 

  • Ansell, Brendan. Introduction to R - tidyverse. 

  • Dalpiaz. Applied Statistics with R. 

  • 小池祐太  (2017) 統計データ解析Ⅰ，(2018) 統計データ解析 Ⅱ，東大OCW．

  • 森知晴 (2021) 卒業論文のためのR入門．

  • 矢内勇生 (2020) KUT 計量経済学応用―統計的因果推論入門．

  • 安藤道人，三田匡能 (2023) Rで学ぶ計量経済学と機械学習．

  • 土井翔平 (2023) Rで計量政治学入門．

  • 宋財泫，矢内勇生 (2023) 私たちのR―ベストプラクティスの探求．

• Datasets related to social sciences

  • IPUMS (International Integrated Public Use Microdata Series)

  • 政府統計の総合窓口（e-Stat）, 総務省統計局・独立行政法人統計センター

  • 国土数値情報 (行政区域，鉄道，道路，河川，地価公示，土地利用メッシュ，公共施設，他), 国土交通省

  • 東京都オープンデータカタログ (防災，犯罪，インフラ・まちづくり，人口，福祉，他), 東京都

  • JDCat (人文学・社会科学総合データカタログ), 日本学術振興会

  • SSJデータアーカイブ (労働調査，社会調査の個票データ), 東京大学社会科学研究所附属社会調査・データアーカイブ研究センター

  • Primer: Where to find data, Sebastian Tello-Trillo

  • Economics Data Resources, University of Minnesota

  • A dataset with political datasets, Erik Larsen

  • Links to Data Sets and Repositories, American Psychological Association

  • 研究上のtipsあれこれ: データ収集, 高野佳佑

  • Kaggle / Useful for finding datasets to exercise data analysis

• Replication file of published paper (limited to te field of social sciences)

  • Find Economic Articles with Data by Sebastian Kranz

  • openICPSR (American Economic Review, American Economic Journal, etc.)

  • Harvard Dataverse (Quarterly Journal of Economics, Review of Economics and Statistics, etc.)

  • Zenodo (Review of Economic Studies, etc.)

  • Mendeley Data (Journal of Public Economics, etc.)

  • ZBW Journal Data Archive (Journal of Applied Econometrics, etc.)

  • Find Replication Data by Journal ... Covering political science journals (AJPS, etc.)

  • Journal of Accounting Research: Online Supplements and Datasheets / Programs for calculations are provided in many papers, but data are scarce.