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Related Concept Videos

Sampling Plans01:23

Sampling Plans

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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...
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Convenience Sampling Method00:55

Convenience Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
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Stratified Sampling Method01:16

Stratified Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
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Cluster Sampling Method01:20

Cluster Sampling Method

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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
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Random Sampling Method01:09

Random Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
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What are Populations and Communities?00:30

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Related Experiment Video

Updated: Apr 27, 2026

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools
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[A comparative study of different sampling designs in fish community estimation].

Jing Zhao, Shou-Yu Zhang, Jun Lin

    Ying Yong Sheng Tai Xue Bao = the Journal of Applied Ecology
    |July 12, 2014
    PubMed
    Summary

    For effective fishery management, stratified random sampling offers the best data for fish communities. This method provides more accurate and precise results compared to stationary or simple random sampling.

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    Area of Science:

    • Ecology
    • Fisheries Science
    • Statistical Ecology

    Background:

    • Effective fishery management relies on high-quality data from well-designed sampling programs.
    • Optimal sampling designs must be cost-efficient and significantly impact resource management decisions.

    Purpose of the Study:

    • To compare the performance of stationary sampling, simple random sampling, and stratified random sampling for estimating fish communities.
    • To evaluate sampling designs based on design effect (De), relative error (REE), and relative bias (RB) using computer simulations.

    Main Methods:

    • Computer simulation was employed to compare three sampling designs: stationary, simple random, and stratified random sampling.
    • Performance metrics included design effect (De), relative error (REE), and relative bias (RB).

    Main Results:

    • Stationary sampling exhibited a significantly higher average design effect (3.37) compared to simple random and stratified random sampling (0.961).
    • Stratified random sampling demonstrated superior performance across all metrics (De, REE, RB).
    • Increasing sample size for stratified random sampling reduced design effect and enhanced precision and accuracy.

    Conclusions:

    • Stratified random sampling is the most effective design for estimating fish communities, offering better precision and accuracy.
    • The findings highlight the importance of selecting appropriate sampling strategies for robust fisheries research and management.