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Related Concept Videos

Estimating Population Standard Deviation01:26

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When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
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In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
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Demes: a standard format for demographic models.

Graham Gower1, Aaron P Ragsdale2, Gertjan Bisschop3

  • 1Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, 1350 Copenhagen K, Denmark.

Genetics
|September 29, 2022
PubMed
Summary
This summary is machine-generated.

A new data model called Demes standardizes the description of complex population genetic models. This format simplifies sharing and implementing demographic models across different research tools, accelerating population genetics studies.

Keywords:
demographic modelsinferencesimulation

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Area of Science:

  • Population genetics
  • Computational biology
  • Bioinformatics

Background:

  • Understanding population demographic history is crucial in population genetics.
  • Current demographic models are complex, requiring numerous parameters and lacking a standard definition.
  • This lack of standardization hinders progress and introduces errors in translating models for simulators.

Purpose of the Study:

  • To introduce the Demes data model and file format for defining population genetic models.
  • To address the need for a standardized, unambiguous, and easily implementable format for demographic models.
  • To facilitate the integration of demographic models into population genetic software.

Main Methods:

  • Development of the Demes data model and a corresponding text file format.
  • Implementation of Demes parsers in multiple programming languages (Python, C).
  • Demonstration of Demes support in population genetic simulators and inference methods.

Main Results:

  • Demes provides a well-defined and unambiguous model for populations, their properties, and demographic events.
  • The Demes file format is designed for simplicity and clarity.
  • Tested implementations and initial support in key population genetics software are available.

Conclusions:

  • The Demes data model and file format offer a standardized solution for describing complex demographic models.
  • Demes simplifies the process of using demographic models in population genetic research.
  • This standardization is expected to accelerate research and improve reproducibility in the field.