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Natur- und Sozialwissenschaften · Berufliche Fähigkeiten & Kompetenzen · SOC 19-3011 · 457 Skills

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▶3 typische Aufgaben aus O*NET

Study economic and statistical data in area of specialization, such as finance, labor, or agriculture.
Compile, analyze, and report data to explain economic phenomena and forecast market trends, applying mathematical models and statistical techniques.
Study the socioeconomic impacts of new public policies, such as proposed legislation, taxes, services, and regulations.

Die Aufgabendaten sind der O*NET® 29.1 Database der USDOL/ETA entnommen und werden gemäß CC BY 4.0 verwendet.

aiming-lab/AutoResearchClaw

Statistical methods for combining results across multiple studies. Use when aggregating cross-study or cross-experiment results.

workflows-ideate

brycewang-stanford/Auto-Empirical-Research-Skills

Divergent research ideation — generate many candidate directions, then adversarially filter to the strongest

brycewang-stanford/Auto-Empirical-Research-Skills

Transform research descriptions into well-structured implementation plans following project conventions

workflows-review

brycewang-stanford/Auto-Empirical-Research-Skills

Run multi-agent econometric review on estimation code, identification arguments, and research artifacts

brycewang-stanford/Auto-Empirical-Research-Skills

Execute research implementation plans efficiently while maintaining estimation quality and finishing features

brycewang-stanford/Auto-Empirical-Research-Skills

End-to-end R data analysis workflow from exploration through regression to publication-ready tables and figures

education-data-source-eada

brycewang-stanford/Auto-Empirical-Research-Skills

EADA — college athletics gender equity (~2,000+ institutions, 2002-2021). Participation, coaching, salaries, expenses, revenues, athletic aid by gender. Not Title IX compliance data. No sector column; join IPEDS on unitid for institution type.

education-data-source-edfacts

brycewang-stanford/Auto-Empirical-Research-Skills

EDFacts — K-12 outcomes: assessment proficiency, ACGR graduation rates, ESSA accountability at school/district level (2009-2020). Within-state trends and subgroup gaps. Complements CCD with outcome data. Cannot compare across states — use NAEP.

education-data-source-fsa

brycewang-stanford/Auto-Empirical-Research-Skills

FSA — Title IV aid at institution level (~5,500 institutions, 1999-2021). Pell Grants, Direct/PLUS loans, campus-based aid, financial responsibility scores, 90/10 metrics. Use for aid distribution, loan volume, or for-profit analysis. By unitid.

education-data-source-ipeds

brycewang-stanford/Auto-Empirical-Research-Skills

IPEDS — primary federal postsecondary data (~6,500 institutions, 1980-present): enrollment, completions, graduation rates, finance, aid, admissions, HR. For college/university analysis. Grad rates = first-time full-time; finance needs GASB/FASB care.

education-data-source-meps

brycewang-stanford/Auto-Empirical-Research-Skills

MEPS — Urban Institute modeled school-level poverty (% at 100% FPL), from CCD + SAIPE (public schools, 2009-2022, 2-3yr lag). Use when FRPL is unreliable due to CEP. Consistent cross-state measurement. Public schools only.

education-data-source-nacubo

brycewang-stanford/Auto-Empirical-Research-Skills

NACUBO endowment data (~650 institutions, 2012-2022). Portal: 7 columns only (total endowment, per-FTE, YoY change). Use for endowment size/trends. Full investment/spending needs direct NACUBO access. For all-institution coverage use IPEDS finance.