- Examples by chapters
- 1 Introduction
- 2 Data and measurement
- 3 Some basic methods in mathematics and probability
- 4 Generative models and statistical inference
- 5 Simulation
- 6 Background on regression modeling
- 7 Linear regression with a single predictor
- 8 Fitting regression models
- 9 Prediction and Bayesian inference
- 10 Linear regression with multiple predictors
- 11 Assumptions, diagnostics, and model evaluation
- 12 Transformations
- 13 Logistic regression
- 14 Working with logistic regression
- 15 Other generalized linear models
- 16 Design and sample size decisions
- 17 Poststratification and missing-data imputation
- 18 Causal inference basics and randomized experiments
- 19 Causal inference using regression on the treatment variable
- 20 Observational studies with all confounders assumed to be measured
- 21 More advanced topics in causal inference
- 22 Advanced regression and multilevel models
- A Computing in R
- Examples alphabetically
This repository contains Tidyverse implementations of examples from Regression and Other Stories by Andrew Gelman, Jennifer Hill, and Aki Vehtari (2020).
- Book website
- Original code provided with book
Tidyverse version by Bill Behrman.
- ElectionsEconomy/
- hibbs_tv.md - Predicting presidential vote share from the economy
- ElectricCompany/
- electric_tv.md - Analysis of “Electric Company” data
- Peacekeeping/
- peace_tv.md - Outcomes after civil war in countries with and without United Nations peacekeeping
- SimpleCausal/
- causal_tv.md - Simple graphs illustrating regression for causal inference
- Helicopters/
- helicopters_tv.md - Example data file for helicopter flying time exercise
- HDI/
- hdi_tv.md - Human Development Index - Looking at data in different ways
- Pew/
- pew_tv.md - Miscellaneous analyses using raw Pew data
- HealthExpenditure/
- healthexpenditure_tv.md - Discovery through graphs of data and models
- Names/
- lastletters_tv.md - Last letters - Distributions of last letters of names of American babies
- Congress/
- congress_plots_tv.md - Predictive uncertainty for congressional elections
- AgePeriodCohort/
- births_tv.md - Age adjustment
- Mile/
- mile_tv.md - Trend of record times in the mile run
- Metabolic/
- metabolic_tv.md - How to interpret a power law or log-log regression
- CentralLimitTheorem/
- heightweight_tv.md - Illustrate central limit theorem and normal distribution
- Stents/
- stents_tv.md - Stents - comparing distributions
- Coverage/
- coverage_tv.md - Example of coverage
- Death/
- polls_tv.md - Proportion of American adults supporting the death penalty
- Coop/
- riverbay_tv.md - Example of hypothesis testing
- Girls/
- ProbabilitySimulation/
- probsim_tv.md - Simulation of probability models
- Earnings/
- earnings_bootstrap_tv.md - Bootstrapping to simulate the sampling distribution
- Simplest/
- simplest_tv.md - Linear regression with a single predictor
- Earnings/
- earnings_regression_tv.md - Predict respondents’ yearly earnings using survey data from 1990
- PearsonLee/
- heights_tv.md - The heredity of height. Published in 1903 by Karl Pearson and Alice Lee.
- FakeMidtermFinal/
- simulation_tv.md - Fake dataset of 1,000 students’ scores on a midterm and final exam
- ElectionsEconomy/
- hibbs_tv.md - Predicting presidential vote share from the economy
- hibbs_coverage_tv.md - Checking the coverage of intervals
- Simplest/
- simplest_tv.md - Linear regression with a single predictor
- ElectionsEconomy/
- hills_tv.md - Present uncertainty in parameter estimates
- hibbs_tv.md - Predicting presidential vote share from the economy
- Influence/
- influence_tv.md - Influence of individual points in a fitted regression
- ElectionsEconomy/
- hibbs_tv.md - Predicting presidential vote share from the economy
- bayes_tv.md - Demonstration of Bayesian information aggregation
- Earnings/
- height_and_weight_tv.md - Predict weight
- SexRatio/
- sexratio_tv.md - Example where an informative prior makes a difference
- KidIQ/
- kidiq_tv.md - Linear regression with multiple predictors
- Earnings/
- height_and_weight_tv.md - Predict weight
- Congress/
- congress_tv.md - Predictive uncertainty for congressional elections
- NES/
- nes_linear_tv.md - Fitting the same regression to many datasets
- Beauty/
- beauty_tv.md - Student evaluations of instructors’ beauty and teaching quality
- KidIQ/
- kidiq_tv.md - Linear regression with multiple predictors
- Residuals/
- residuals_tv.md - Plotting the data and fitted model
- Introclass/
- residual_plots_tv.md - Plot residuals vs. predicted values, or residuals vs. observed values?
- Newcomb/
- newcomb_tv.md - Posterior predictive checking of Normal model for Newcomb’s speed of light data
- Unemployment/
- unemployment_tv.md - Time series fit and posterior predictive model checking for unemployment series
- Rsquared/
- rsquared_tv.md - Bayesian R^2
- CrossValidation/
- crossvalidation_tv.md - Demonstration of cross validation
- FakeKCV/
- fake_kcv_tv.md - Demonstration of K-fold cross-validation using simulated data
- Pyth/
- KidIQ/
- kidiq_tv.md - Linear regression with multiple predictors
- Earnings/
- earnings_regression_tv.md - Predict respondents’ yearly earnings using survey data from 1990
- Gay/
- gay_simple_tv.md - Simple models (linear and discretized age) and political attitudes as a function of age
- Mesquite/
- mesquite_tv.md - Predicting the yields of mesquite bushes
- Student/
- student_tv.md - Models for regression coefficients
- Pollution/
- pollution_tv.md - Pollution data
- NES/
- nes_logistic_tv.md - Logistic regression, identifiability, and separation
- LogisticPriors/
- logistic_priors_tv.md - Effect of priors in logistic regression
- Arsenic/
- arsenic_logistic_building_tv.md - Building a logistic regression model: wells in Bangladesh
- Rodents/
- LogitGraphs/
- logitgraphs_tv.md - Different ways of displaying logistic regression
- Arsenic/
- arsenic_logistic_building_tv.md - Building a logistic regression model: wells in Bangladesh
- arsenic_logistic_apc_tv.md - Average predictive comparisons for a logistic regression model: wells in Bangladesh
- arsenic_logistic_residuals_tv.md - Residual plots for a logistic regression model: wells in Bangladesh
- NES/
- nes_logistic_tv.md - Logistic regression, identifiability, and separation
- PoissonExample/
- poisson_regression_tv.md - Demonstrate Poisson regression with simulated data
- Roaches/
- roaches_tv.md - Analyze the effect of integrated pest management on reducing cockroach levels in urban apartments
- Storable/
- storable_tv.md - Ordered categorical data analysis with a study from experimental economics, on the topic of “storable votes”
- Robit/
- robit_tv.md - Comparison of robit and logit models for binary data
- Earnings/
- earnings_compound_tv.md - Compound discrete-continuous model
- RiskyBehavior/
- risky_tv.md Risky behavior data
- NES/
- Lalonde/
- Congress/
- AcademyAwards/
- SampleSize/
- simulation_tv.md - Sample size simulation
- FakeMidtermFinal/
- simulation_based_design_tv.md - Fake dataset of a randomized experiment on student grades
- ElectricCompany/
- electric_tv.md - Analysis of “Electric Company” data
- Poststrat/
- poststrat_tv.md - Poststratification after estimation
- poststrat2_tv.md - Poststratification after estimation
- Imputation/
- imputation_tv.md - Regression-based imputation for the Social Indicators Survey
- Sesame/
- sesame_tv.md - Causal analysis of Sesame Street experiment
- ElectricCompany/
- electric_tv.md - Analysis of “Electric Company” data
- Incentives/
- incentives_tv.md - Simple analysis of incentives data
- Cows/
- ElectricCompany/
- electric_tv.md - Analysis of “Electric Company” data
- Childcare/
- childcare_tv.md - Infant Health and Development Program (IHDP) example
- Lalonde/
- Sesame/
- sesame_tv.md - Causal analysis of Sesame Street experiment
- ChileSchools/
- chile_schools_tv.md - ChileSchools example.
- Bypass/
- Golf/
- golf_tv.md - Gold putting accuracy: Fitting a nonlinear model using Stan
- Gay/
- gay_tv.md - Nonlinear models (LOESS and spline) and political attitudes as a function of age
- ElectionsEconomy/
- hibbs_tv.md - Predicting presidential vote share from the economy
- Scalability/
- scalability_tv.md - Demonstrate computation speed with 100,000 observations
- Coins/
- Mile/
- mile_tv.md - Trend of record times in the mile run
- Earnings/
- earnings_data_tv.md - Read in and prepare earnings data
- Parabola/
- parabola_tv.md - Demonstration of using Stan for optimization
- Restaurant/
- restaurant_tv.md - Demonstration of using Stan for optimization
- DifferentSoftware/
- linear_tv.md - Linear regression using different software options
- AcademyAwards/
- AgePeriodCohort/
- births_tv.md - Age adjustment
- Arsenic/
- arsenic_logistic_building_tv.md - Building a logistic regression model: wells in Bangladesh
- arsenic_logistic_apc_tv.md - Average predictive comparisons for a logistic regression model: wells in Bangladesh
- arsenic_logistic_residuals_tv.md - Residual plots for a logistic regression model: wells in Bangladesh
- Beauty/
- beauty_tv.md - Student evaluations of instructors’ beauty and teaching quality
- Bypass/
- CentralLimitTheorem/
- heightweight_tv.md - Illustrate central limit theorem and normal distribution
- Childcare/
- childcare_tv.md - Infant Health and Development Program (IHDP) example
- ChileSchools/
- chile_schools_tv.md - ChileSchools example.
- Coins/
- Congress/
- congress_tv.md - Predictive uncertainty for congressional elections
- congress_plots_tv.md - Predictive uncertainty for congressional elections
- Coop/
- riverbay_tv.md - Example of hypothesis testing
- Coverage/
- coverage_tv.md - Example of coverage
- Cows/
- CrossValidation/
- crossvalidation_tv.md - Demonstration of cross validation
- Death/
- polls_tv.md - Proportion of American adults supporting the death penalty
- DifferentSoftware/
- linear_tv.md - Linear regression using different software options
- Earnings/
- earnings_bootstrap_tv.md - Bootstrapping to simulate the sampling distribution
- earnings_compound_tv.md - Compound discrete-continuous model
- earnings_regression_tv.md - Predict respondents’ yearly earnings using survey data from 1990
- height_and_weight_tv.md - Predict weight
- earnings_data_tv.md - Read in and prepare earnings data
- ElectionsEconomy/
- bayes_tv.md - Demonstration of Bayesian information aggregation
- hibbs_coverage_tv.md - Checking the model-fitting procedure using fake-data simulation.
- hibbs_tv.md - Predicting presidential vote share from the economy
- hills_tv.md - Present uncertainty in parameter estimates
- ElectricCompany/
- electric_tv.md - Analysis of “Electric Company” data
- FakeKCV/
- fake_kcv_tv.md - Demonstration of K-fold cross-validation using simulated data
- FakeMidtermFinal/
- simulation_tv.md - Fake dataset of 1,000 students’ scores on a midterm and final exam
- simulation_based_design_tv.md - Fake dataset of a randomized experiment on student grades
- Gay/
- gay_simple_tv.md - Simple models (linear and discretized age) and political attitudes as a function of age
- gay_tv.md - Nonlinear models (LOESS and spline) and political attitudes as a function of age
- Girls/
- Golf/
- golf_tv.md - Gold putting accuracy: Fitting a nonlinear model using Stan
- HDI/
- hdi_tv.md - Human Development Index - Looking at data in different ways
- HealthExpenditure/
- healthexpenditure_tv.md - Discovery through graphs of data and models
- Helicopters/
- helicopters_tv.md - Example data file for helicopter flying time exercise
- Imputation/
- imputation_tv.md - Regression-based imputation for the Social Indicators Survey
- Incentives/
- incentives_tv.md - Simple analysis of incentives data
- Influence/
- influence_tv.md - Influence of individual points in a fitted regression
- Introclass/
- residual_plots_tv.md - Plot residuals vs. predicted values, or residuals vs. observed values?
- KidIQ/
- kidiq_tv.md - Linear regression with multiple predictors
- Lalonde/
- LogisticPriors/
- logistic_priors_tv.md - Effect of priors in logistic regression
- LogitGraphs/
- logitgraphs_tv.md - Different ways of displaying logistic regression
- Mesquite/
- mesquite_tv.md - Predicting the yields of mesquite bushes
- Metabolic/
- metabolic_tv.md - How to interpret a power law or log-log regression
- Mile/
- mile_tv.md - Trend of record times in the mile run
- Names/
- lastletters_tv.md - Last letters - Distributions of last letters of names of American babies
- NES/
- nes_linear_tv.md - Fitting the same regression to many datasets
- nes_logistic_tv.md - Logistic regression, identifiability, and separation
- Newcomb/
- newcomb_tv.md - Posterior predictive checking of Normal model for Newcomb’s speed of light data
- Parabola/
- parabola_tv.md - Demonstration of using Stan for optimization
- Peacekeeping/
- peace_tv.md - Outcomes after civil war in countries with and without United Nations peacekeeping
- PearsonLee/
- heights_tv.md - The heredity of height. Published in 1903 by Karl Pearson and Alice Lee.
- Pew/
- pew_tv.md - Miscellaneous analyses using raw Pew data
- PoissonExample/
- poisson_regression_tv.md - Demonstrate Poisson regression with simulated data
- Pollution/
- pollution_tv.md - Pollution data
- Poststrat/
- poststrat_tv.md - Poststratification after estimation
- poststrat2_tv.md - Poststratification after estimation
- ProbabilitySimulation/
- probsim_tv.md - Simulation of probability models
- Pyth/
- Residuals/
- residuals_tv.md - Plotting the data and fitted model
- Restaurant/
- restaurant_tv.md - Demonstration of using Stan for optimization
- RiskyBehavior/
- risky_tv.md Risky behavior data
- Roaches/
- roaches_tv.md - Analyze the effect of integrated pest management on reducing cockroach levels in urban apartments
- Robit/
- robit_tv.md - Comparison of robit and logit models for binary data
- Rodents/
- Rsquared/
- rsquared_tv.md - Bayesian R^2
- SampleSize/
- simulation_tv.md - Sample size simulation
- Scalability/
- scalability_tv.md - Demonstrate computation speed with 100,000 observations
- Sesame/
- sesame_tv.md - Causal analysis of Sesame Street experiment
- SexRatio/
- sexratio_tv.md - Example where an informative prior makes a difference
- SimpleCausal/
- causal_tv.md - Simple graphs illustrating regression for causal inference
- Simplest/
- simplest_tv.md - Linear regression with a single predictor
- Stents/
- stents_tv.md - Stents - comparing distributions
- Storable/
- storable_tv.md - Ordered categorical data analysis with a study from experimental economics, on the topic of “storable votes”
- Student/
- student_tv.md - Models for regression coefficients
- Unemployment/
- unemployment_tv.md - Time series fit and posterior predictive model checking for unemployment series
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