Refine
Year of publication
Document Type
- Preprint (664)
- Article (366)
- Working Paper (1)
Has Fulltext
- yes (1031)
Is part of the Bibliography
- no (1031)
Keywords
- Heavy Ion Experiments (20)
- Hadron-Hadron Scattering (11)
- Hadron-Hadron scattering (experiments) (11)
- LHC (9)
- Heavy-ion collision (6)
- ALICE experiment (4)
- Collective Flow (4)
- Jets (4)
- Quark-Gluon Plasma (4)
- ALICE (3)
- Heavy Ions (3)
- Jets and Jet Substructure (3)
- pp collisions (3)
- Beauty production (2)
- Charm physics (2)
- Experimental nuclear physics (2)
- Experimental particle physics (2)
- Heavy Quark Production (2)
- Lepton-Nucleon Scattering (experiments) (2)
- Particle Correlations and Fluctuations (2)
- Particle and resonance production (2)
- Particle correlations and fluctuations (2)
- Pb–Pb collisions (2)
- QCD (2)
- Single electrons (2)
- 900 GeV (1)
- ALICE detector (1)
- Anti-nuclei (1)
- Antifungal agents (1)
- Aspergillosis (1)
- Boosted Jets (1)
- COVID-19 (1)
- Centrality Class (1)
- Centrality Selection (1)
- Collective Flow, (1)
- Comparison with QCD (1)
- Electron-pion identification (1)
- Electroweak interaction (1)
- Elliptic flow (1)
- Everolimus resistance (1)
- Femtoscopy (1)
- Fibre/foam sandwich radiator (1)
- Forschung (1)
- HBT (1)
- HDAC-inhibition (1)
- HNO (1)
- Hadron production (1)
- Hadron-Hadron Scattering Heavy (1)
- Hadron-hadron interactions (1)
- Hals-Nasen-Ohren-Heilkunde (1)
- Hard Scattering (1)
- Heavy Ion Experiment (1)
- Heavy flavor production (1)
- Heavy flavour production (1)
- Heavy ions (1)
- Heavy-flavour decay muons (1)
- Heavy-flavour production (1)
- Heavy-ion collisions (1)
- Hematologic malignancies (1)
- Inclusive spectra (1)
- Intensity interferometry (1)
- Invariant Mass Distribution (1)
- Invasive candidiasis (1)
- Ionisation energy loss (1)
- Jet Physics (1)
- Jet Substructure (1)
- Lehre (1)
- Material budget (1)
- Mid-rapidity (1)
- Minimum Bias (1)
- Monte Carlo (1)
- Multi-Parton Interactions (1)
- Multi-strange baryons (1)
- Multi-wire proportional drift chamber (1)
- Mycoses (1)
- Neural network (1)
- Nuclear modification factor (1)
- ORL (1)
- Otorhinolaryngology (1)
- PYTHIA (1)
- Particle and Resonance Production (1)
- Pb–Pb (1)
- Production Cross Section (1)
- Properties of Hadrons (1)
- Proton–proton (1)
- Quark Deconfinement (1)
- Quark Gluon Plasma (1)
- Quark Production (1)
- Quark gluon plasma (1)
- Quarkonium (1)
- Rapidity Range (1)
- Relativistic heavy ion physics (1)
- Relativistic heavy-ion collisions (1)
- Renal cell carcinoma (1)
- Research (1)
- Residency (1)
- Resolution Parameter (1)
- SARS-CoV‑2 pandemic (1)
- SARS-CoV‑2-Pandemie (1)
- Single muons (1)
- Specialist training (1)
- Systematic Uncertainty (1)
- TR (1)
- Teaching (1)
- Time Projection Chamber (1)
- Tracking (1)
- Transition radiation detector (1)
- Transverse momentum (1)
- Trigger (1)
- Tumor growth (1)
- University hospitals (1)
- Universitätskliniken (1)
- Vector Boson Production (1)
- Weiterbildung (1)
- Xenon-based gas mixture (1)
- cdk2/cyclin A (1)
- central nervous system infection (1)
- dE/dx (1)
- detector (1)
- diagnosis (1)
- experimental results (1)
- guideline (1)
- heavy ion experiments (1)
- immunocompromised patient (1)
- quark gluon plasma (1)
- spectra (1)
- treatment (1)
- √sN N = 2.76 TeV (1)
Institute
- Physik (1024)
- Frankfurt Institute for Advanced Studies (FIAS) (954)
- Informatik (920)
- Medizin (5)
- Informatik und Mathematik (3)
- Hochschulrechenzentrum (2)
- Center for Financial Studies (CFS) (1)
- House of Finance (HoF) (1)
- Sustainable Architecture for Finance in Europe (SAFE) (1)
- Wirtschaftswissenschaften (1)
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.