brycewang-stanford/Auto-Empirical-Research-Skills - Page 17

interactive-viz-guide

Interactive data visualization with Plotly, ECharts, and D3

metabase-analytics-guide

Guide to Metabase for open-source research data analytics and dashboards

network-visualization-guide

Visualize networks, graphs, citation maps, and relational data

plotly-interactive-guide

Guide to Plotly.py for interactive scientific visualizations in Python

publication-figures-guide

Create journal-quality scientific figures with proper styling and accessibility

python-dataviz-guide

Publication-quality data visualization with matplotlib, seaborn, and plotly

redash-analytics-guide

Guide to Redash for SQL-driven research data dashboards and sharing

dataviz-skills

14 data visualization skills. Trigger: charts, plots, figures, publication-quality graphics. Design: one skill per tool with code templates and academic formatting conventions.

causal-inference-guide

Causal inference methods including DiD, IV, RDD, and synthetic control

econml-causal-guide

Apply EconML for causal inference combining machine learning and econometrics

iv-regression-guide

Apply instrumental variables, 2SLS, and address endogeneity issues

mostly-harmless-guide

Replication code and guide for Mostly Harmless Econometrics methods

panel-data-analyst

Expert panel data regression analysis with fixed effects and GMM

panel-data-guide

Panel data analysis with fixed and random effects models

python-causality-guide

Learn causal inference with Python using the Brave and True handbook

robustness-checks

Sequential robustness checks in Stata with confounder blocks

econometrics-skills

12 econometrics skills. Trigger: causal analysis, regression models, treatment effects, panel data. Design: method-centric guides with R/Python code and diagnostic tests.

stata-accounting-guide

STATA code for empirical accounting and financial economics research

stata-analyst-guide

Stata workflows for publication-ready sociology and social science research

stata-reference-guide

Comprehensive Stata reference covering syntax, econometrics, and 20+ packages

time-series-guide

Apply ARIMA, VAR, cointegration, and time series econometric methods

bayesian-statistics-guide

Bayesian inference methods including prior selection, MCMC, and model comparison

data-anomaly-detection

Detect anomalies and outliers in research data using statistical methods

hypothesis-testing-guide

Statistical hypothesis testing, power analysis, and significance reporting

meta-analysis-guide

Conduct systematic meta-analyses with effect size pooling and heterogeneity

ml-experiment-tracker

Plan reproducible ML experiment runs with parameters and metrics tracking

modeling-strategy-guide

Strategic statistical modeling, experimentation, and causal inference

nonparametric-tests-guide

Apply Mann-Whitney, Kruskal-Wallis, and other nonparametric methods

power-analysis-guide

Sample size calculation and statistical power analysis guide

sem-guide

Structural equation modeling with latent variables guide

statistics-skills

10 statistical analysis skills. Trigger: statistical tests, Bayesian analysis, hypothesis testing, sampling. Design: method guides covering assumptions, code, and result interpretation.

survival-analysis-guide

Conduct Kaplan-Meier, Cox regression, and time-to-event analyses

csv-data-analyzer

Load, explore, clean, and analyze CSV data with statistical summaries

data-cleaning-pipeline

Systematic data cleaning workflows for research datasets

data-cog-guide

Upload messy CSVs with minimal prompting for deep automated analysis

missing-data-handling

Diagnose missing data patterns and apply appropriate imputation strategies

pandas-data-wrangling

Data cleaning, transformation, and exploratory analysis with pandas

questionnaire-design-guide

Questionnaire and survey design with Likert scales and coding

wrangling-skills

10 data wrangling skills. Trigger: messy data, format conversion, missing values, data reshaping. Design: pipeline-oriented recipes for common data cleaning and transformation tasks.

stata-data-cleaning

Clean, transform, and validate messy research data using Stata