Ридинг лист по конкретным методам находится тут (пока это очень черновая неразобранная версия).
- Literature on Recent Advances in Applied Micro Methods (Christine Cai, 2022)
- Collection of lecture notes, videos, papers, workshops, etc. (Asjad Naqvi )
- Введение в прикладную статистику и эконометрику (Архангельский, 2016)
- Topics in Causal Inference (Архангельский, 2018)
- Intro into Panel Data Methods (Архангельский, 2020)
- Intro to Experimental Analysis (Архангельский, 2021)
- Causal Inference: The Mixtape (Scott Cunningham, 2021)
- Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction. (Guido Imbens, Donald Rubin, 2015)
- A First Course in Causal Inference (Peng Ding, 2023)
- Causal Inference: What If (Miguel Hernan, Jamie Robins, 2020)
- Applied Causal Inference Powered by ML and AI (Victor Chernozhukov, Christian Hansen, Nathan Kallus, Martin Spindler, Vasilis Syrgkanis, 2024)
- Introduction to Causal Inference (Brady Neal, 2020)
- The Effect: An Introduction to Research Design and Causality (Nick Huntington-Klein, 2022)
- Causal Inference for The Brave and True (Matheus Facure)
- Research Design in the Social Sciences (Declaration, Diagnosis, Redesign)
- Mostly Harmess Econometrics (Joshua D. Angrist, Jörn-Steffen Pischke)
- Mastering ‘Metrics (Joshua D. Angrist, Jörn-Steffen Pischke)
- Statistical Tools for Causal Inference (Sylvain Chabé-Ferret, 2022)
- Counterfactuals and Causal Inference. Methods and Principles for Social Research (Stephen L. Morgan, Christopher Winship, 2007)
- The Theory and Practice of Field Experiments: An Introduction from the EGAP Learning Days
- Using R for introductory econometrics (Heiss, 2016)
- Causality (Judea Pearl, 2009)
- Causal inference in statistics (Judea Pearl, Madelyn Glymour, Nicholas P. Jewell, 2016)
- The book of why: the new science of cause and effect (Judea Pearl, Dana Mackenzie, 2018)
- A Guide on Data Analysis
- Marketing Research
- Introduction to Causal Inference from a Machine Learning Perspective (Brady Neal, 2020)
- The Effect. Econometrics, Causality, and Coding with Dr. HK (Nick Huntington-Klein)
- Econometrics, Causality, and Coding with Dr. HK (Nick Huntington-Klein)
- Causal Inference -- Online Lectures (M.Sc/PhD Level) (Ben Elsner)
- Visualization, Identification, and Estimation in the Linear Panel Event-Study Design (Jesse Shapiro, Christian Hansen)
- Applied Methods PhD Course (Paul Goldsmith-Pinkham, 2021)
- DiD Reading Group (Taylor Wright) и Other DiD Seminars
- Introduction to Econometrics (Ivan A. Canay, 2021)
- Topics in Econometric Theory (Ivan A. Canay, 2021)
- NBER SI 2024 Methods Lecture: New Developments in Experimental Design and Analysis
- Analysis and Design of Multi-Armed Bandit Experiments and Policy Learning (Susan Athey)
- Interference and Spillovers in Randomized Experiments (Guido Imbens)
- Mastering Mostly Harmless Econometrics (Alberto Abadie, Joshua Angrist, and Christopher Walters, 2020)
- Cross-Section Econometrics (Alberto Abadie, Joshua Angrist, Christopher Walters, 2017)
- Time Series Econometrics (James H. Stock and Mark W. Watson, 2015)
- Сross-Section Econometrics (Alberto Abadie and Joshua Angrist, 2014)
- Time Series Econometrics (Giorgio Primiceri and Frank Schorfheide, 2013)
- Cross-section Econometrics (Guido Imbens and Jeffrey Wooldridge, 2012)
- Time-Series Econometrics (James H. Stock and Mark W. Watson, 2010)
- Cross-Section Econometrics (Jeffrey Wooldridge and Guido Imbens, 2009)
- Mixtape-Sessions (Scott Cunningham)
- PhD Applied Econometrics (Kirill Borusyak, 2023)
- Introduction to Causal Inference (Brady Neal, 2020)
- Causal Inference with Applications (Kosuke Imai, 2021)
- Causal Inference with Applications (Matthew Blackwell, 2021)
- Causal Inference for the Social Sciences (Jasjeet S. Sekhon, 2015)
- Program Evaluation for Public Service (Andrew Heiss, 2020)
- Class material in Statistics and Econometrics (Paolo Zacchia)
- Introduction to Statistics with Computer Applications (Kyle F Butts)
- Applied Empirical Methods (Paul Goldsmith-Pinkham)
- Applied Econometrics at NYU Stern (Chris Conlon)
- Data Science for Business Applications (Magdalena Bennett)
- Probability and Statistics / Econometric Theory / Microeconometrics (Paolo Zacchia)
- Graduate econometrics (Ivan A. Canay)
- Topics in Econometrics (Ivan A. Canay)
- Causal Inference (Stefan Wager)
- Econometrics (Undergraduate)(Daniele Girardi)
- Introduction to Probability and Statistics (Kyle Butts)
- Causal AI Blog (Brady Neal)
- Causal Analysis in Theory and Practice
- Nick Huntington-Klein
- Christine Cai
- Andrew Baker
- Paul Goldsmith-Pinkham
- David Schönholzer
- Разведывательный анализ данных с помощью языка R (Пензар Д, Жарикова А., Валяева А., 2023)
- Основы программирования на R (Антонов А., 2021)
- Анализ данных в R (Иванчей И., Карпов А., 2023)
- Анализ данных в R. Часть 2 (Карпов А., Грозин В., Антонов А., 2023)
- Язык R для пользователей Excel (Алексей Селезнёв, 2022)
- Введение в dplyr 1.0.0 (Алексей Селезнёв, 2023)
- Курс ‘Циклы и функционалы в языке R’ (Алексей Селезнёв, 2022)
- Разработка telegram ботов на языке R (Алексей Селезнёв, 2024)
- Курс "Язык R для интернет маркетинга" (Алексей Селезнёв, 2022)
- Курс 'Разработка пакетов на языке R' (Алексей Селезнёв, 2023)
- Анализ данных и статистика в R (Иван Поздняков, 2024)
- R Intro (Филипп Управителев, 2022)
- Заметки по R (Борис Демешев, 2016)
- Анализ данных и машинное обучение для исследователей (Ангельгардт, 2023)
- Статистика, R и анализ данных (Поздняков Иван, Петухова Татьяна, 2020)
- Наука о данных в R для программы Цифровых гуманитарных исследований (Георгий Мороз)
- Анализ временных рядов с помощью R (Сергей Мастицкий, 2020)
- Классификация, регрессия и другие алгоритмы Data Mining с использованием R (Шитиков В. К., Мастицкий С. Э., 2017)
- Визуализация и анализ географических данных на языке R (Тимофей Самсонов, 2023)
- Пространственная статистика на языке R (Тимофей Самсонов, 2023)
- Наглядная статистика. Используем R! (А. Б. Шипунов и др., 2014)
- Статистический анализ данных в системе R (А. Г. Буховец и др., 2010)
- Статистический анализ и визуализация данных с помощью R (Мастицкий С. Э., Шитиков В. К., 2015)
- R for Data Science (Garrett Grolemund, Hadley Wickham, 2023)
- R Cookbook (Paul Teetor, 2019)
- Advanced R (Hadley Wickham, 2019)
- Advanced R Solutions (Malte Grosser, Malte Grosser, Hadley Wickham, 2019)
- R Packages (Hadley Wickham, Jennifer Bryan, 2023)
- An Introduction to R. Notes on R: A Programming Environment for Data Analysis and Graphics (W. N. Venables, D. M. Smith, 2022)
- Using R for Introductory Econometrics (Florian Heiss, 2020)
- Guide to R For SCU Economics Students (William A. Sundstrom, Michael J. Kevane)
- Introduction to Econometrics with R (Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer)
- R for Data Science (Hadley Wickham, Garrett Grolemund)
- Hands-On Programming with R (Garrett Grolemund)
- Data Science: A First Introduction (Tiffany Timbers, Trevor Campbell, and Melissa Lee)
- YaRrr! The Pirate’s Guide to R (Nathaniel D. Phillips)