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Error Bars for Distributions of Numbers of Events

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Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
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Ritu Aggarwal, Allen Caldwell

Data Analysis, Statistics and Probability · Submitted 12 Dec 2011

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim The common practice for displaying error bars on distributions of numbers of events is confusing and can lead to incorrect conclusions.

how it is stated · asserted 0.92 read the record →

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arXiv ID1112.2593 (version 3)
Pith IDQHU2N4CV, Pith's permanent record of this paper and its review
CitationAllen Caldwell, Ritu Aggarwal. "Error Bars for Distributions of Numbers of Events." arXiv:1112.2593 (2011). https://pith.science/paper/QHU2N4CV
Claim paper

The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

Open the compiled record

Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 2,215 input tokens, $0.0001 reported.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.07 · human participants 0.04 · controlled comparison 0.06 · randomized assignment 0.02 · states quantitative result 0.03 · compares with prior results 0.49 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v3. Results and the main claim are underlined; .

The common practice for displaying error bars on distributions of numbers of events is confusing and can lead to incorrect conclusions. A proposal is made for a different style of presentation that more directly indicates the level of agreement between expectations and observations.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 The common practice for displaying error bars on distributions of numbers of events is confusing and can lead to incorrect conclusions. background 0.94 0.13 0.42 asserted 0.92
s1 A proposal is made for a different style of presentation that more directly indicates the level of agreement between expectations and observations. contribution 0.99 0.77 0.34 asserted 0.86

What kind of paper the classifier reports this is: method or tool 0.51 · evidence from argument 1.00.

What was examined, and what was not

sources read
  • arXiv listing abstract v3
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

The common practice for displaying error bars on distributions of numbers of events is confusing and can lead to incorrect conclusions. A proposal is made for a different style of presentation that more directly indicates the level of agreement between expectations and observations.

Human review

How Pith checks papers → · Full audit of this paper →

How the literature uses it

1 arXiv paper cite this in 1 sentence

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

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