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Related Concept Videos

Sample Size Calculation01:19

Sample Size Calculation

Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
Range00:59

Range

The range is one of the measures of variation. It can be defined as the difference between a dataset's highest and lowest values. For example, in the study of seven 16-ounce soda cans, the filled volume of soda was measured, thus producing the following amount (in ounces) of soda:
15.9; 16.1; 15.2; 14.8; 15.8; 15.9; 16.0; 15.5
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What are Populations and Communities?00:30

What are Populations and Communities?

Populations are groups of individuals of the same species that inhabit a shared environment. Communities include multiple co-existing, interacting populations of different species. Metapopulations span multiple populations of the same species that occupy different areas. Metapopulations interact through immigration and emigration, providing genetic diversity that lends resilience to harsh environments. Population size and density can be estimated using quadrat and mark and recapture...
Sampling Plans01:23

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
Sample Proportion and Population Proportion01:20

Sample Proportion and Population Proportion

Collecting samples or responses from an entire population takes significant time and effort, so a researcher collects responses from only a sample of that population. Suppose a study needs to collect information about a specific mobile application. After sample collection, the researcher analyzes the data and discovers that most individuals in the sample use that specific mobile application. The sample proportion measures the number of individuals in a sample who either use or don't use the...

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Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools
09:32

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

Published on: November 20, 2017

Home range estimates vary with sample size and methods.

Sarah A Boyle1, Waldete C Lourenço, Lívia R da Silva

  • 1Arizona State University, School of Life Sciences, Tempe, Arizona, USA. sarahannboyle@gmail.com

Folia Primatologica; International Journal of Primatology
|February 12, 2009
PubMed
Summary
This summary is machine-generated.

Estimating primate home range is crucial. Minimum convex polygon (MCP) proved more accurate than adaptive kernel (AK) and fixed kernel (FK) methods for northern bearded saki monkeys, especially with small sample sizes.

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Area of Science:

  • Primate ecology
  • Wildlife biology
  • Conservation science

Background:

  • Accurate home range estimation is vital for primate research and conservation.
  • Existing home range estimation methods (MCP, AK, FK) show significant variability in accuracy.
  • Understanding species-specific behavioral ecology is key to selecting appropriate methods.

Purpose of the Study:

  • To evaluate the accuracy of Minimum Convex Polygon (MCP), Adaptive Kernel (AK), and Fixed Kernel (FK) estimators for primate home range.
  • To compare home range estimates for northern bearded saki monkeys (Chiropotes satanas chiropotes) in different habitat types.
  • To determine the influence of sample size on the accuracy of different home range estimation methods.

Main Methods:

  • Comparative analysis of three home range estimation techniques: MCP, AK, and FK.
  • Field study of northern bearded saki monkeys in Brazilian Amazon forest fragments and continuous forest.
  • Assessment of home range and day range estimates based on varying sample sizes.

Main Results:

  • Minimum Convex Polygon (MCP) demonstrated higher accuracy for home and day range estimation compared to AK and FK when sample sizes were small.
  • Adaptive Kernel (AK) frequently overestimated the home range size.
  • Fixed Kernel (FK) also showed limitations in accuracy, particularly with limited data.

Conclusions:

  • The choice of home range estimation method significantly impacts study outcomes.
  • MCP may be more reliable for species like the northern bearded saki monkey with smaller sample sizes.
  • Method selection should consider sample size and the specific behavioral ecology of the target primate species.