Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 670

The DOI matches its Crossref record.

The Use of Probability Paper for the Graphical Analysis of Polymodal Frequency Distributions

Harding, J. P.·1949·Journal of the Marine Biological Association of the United Kingdom

Abstract

The mathematical analysis of bimodal distributions is very complex. Karl Pearson (1894) investigated the problem and developed equations for the purpose; but found them unsolvable as the ‘majority [of the relations] lead to exponential equations the solution of which seems more beyond the wit of man than that of a numerical equation even of the ninth order’. He did indeed evolve an equation of this order and used it to analyse a few bimodal distributions, but the arithmetic involved was very laborious. Later he (Pearson, 1914) gives a table for ‘Constants of normal curve from moments of tail about stump ’which, as he describes in the introduction, occasionally permits a rough analysis of a distribution which is known to be bimodal. This method is much more rapid than the solution of the nonic equation, but ‘owing to the paucity of material in tails and corresponding irregularity there will be large probable errors’. Gottschalk (1948) discusses the question and shows that inthe special case where the bimodal distribution is symmetrical comparatively simple solutions can be found.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1017/s0025315400055259

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Metadata

Authors
Harding, J. P.
Venue
Journal of the Marine Biological Association of the United Kingdom
Published
1949-06
Volume
28
Issue
1
Pages
141-153
ISSN
  • 0025-3154 (ISSN-L)
  • 1469-7769
OpenAlex
W1980609237
Cited by
670
References
0
FWCI
2.18
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: The Use of Probability Paper for the Graphical Analysis of Polymodal Frequency Distributions. https://app.cochat.ai/papers/10.1017/s0025315400055259
The paper
Harding, J. P. (1949). The Use of Probability Paper for the Graphical Analysis of Polymodal Frequency Distributions. Journal of the Marine Biological Association of the United Kingdom. https://doi.org/10.1017/s0025315400055259

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.