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Distributions to Estimate Population Parameter

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The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...

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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 Guinness...

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Related Experiment Video

Updated: May 18, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Capwire: a R package for estimating population census size from non-invasive genetic sampling.

Matthew W Pennell¹, Carisa R Stansbury, Lisette P Waits

¹Institute for Bioinformatics and Evolutionary Studies, University of Idaho, 441B Life Science South, Moscow, ID 83844, USA.

Molecular Ecology Resources

|September 22, 2012

Summary

Non-invasive genetic sampling offers a practical alternative to traditional methods for population studies. The new R package, capwire, provides specialized tools for analyzing genetic data, improving population size estimation for conservation efforts.

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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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A Noninvasive Hair Sampling Technique to Obtain High Quality DNA from Elusive Small Mammals

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Published on: March 13, 2011

Area of Science:

Ecology
Conservation Biology
Population Genetics

Background:

Non-invasive genetic sampling is increasingly vital for wildlife population studies, especially when traditional mark-recapture methods are impractical.
Indirect DNA collection can lead to multiple samples from the same individual within a session, necessitating specialized statistical approaches.
Existing methods may not adequately address the complexities of non-invasive genetic data in population estimation.

Purpose of the Study:

To introduce the R package capwire, designed for population size estimation using non-invasive genetic data.
To provide users with tools for data manipulation and interaction with other R packages.
To enable robust testing and further development of population estimation methods through data simulation.

Main Methods:

Implementation of population size estimators developed by Miller et al. (2005) within the R package capwire.
Development of functions for simulating genetic data under various scenarios to test method robustness.
Facilitation of user interaction with data and existing R packages for genetic analysis.

Main Results:

The capwire package offers a user-friendly implementation of advanced population size estimators.
Simulated data allows for rigorous assessment of the estimators' performance and reliability.
The package supports the ongoing development and application of non-invasive genetic methods in population ecology.

Conclusions:

The capwire R package provides a valuable tool for researchers and conservationists utilizing non-invasive genetic sampling.
It addresses the statistical challenges of multiple captures per individual in population studies.
The package promotes accurate population size estimation and supports informed conservation and management decisions.