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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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Naturalistic Observations02:30

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If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
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Sampling Methods: Overview01:06

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A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
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Sampling Methods: Sample Types01:18

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Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
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Stratified Sampling Method01:16

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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.
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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.
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Related Experiment Video

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Environmental DNA Sampling from Whale-Watching Vessels for Cetacean Monitoring
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Optimal sampling strategies for source identification in environmental episodes.

R Rajagopal1

  • 1Department of Geography, The University of Iowa, USA.

Environmental Monitoring and Assessment
|November 22, 2013
PubMed
Summary
This summary is machine-generated.

This study develops optimal sequential sampling strategies for identifying contamination sources in streams. These methods aid in designing effective water quality surveillance and enforcement systems.

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Area of Science:

  • Environmental Science
  • Water Resource Management
  • Analytical Chemistry

Background:

  • Identifying contamination sources in streams is crucial for environmental protection and public health.
  • Current sampling strategies may not be optimal for diverse stream network configurations.
  • Effective surveillance systems are needed to address water contamination issues.

Purpose of the Study:

  • To develop and describe optimal sequential sampling strategies for pinpointing contamination sources in various stream network setups.
  • To illustrate the application of these strategies to real-world stream water contamination enforcement problems.
  • To discuss the design of surveillance systems and the limitations of existing methods.

Main Methods:

  • Development of novel sequential sampling algorithms tailored for stream networks.
  • Application and illustration of strategies using case studies of stream water contamination.
  • Analysis of information content derived from sequential sampling data.

Main Results:

  • Demonstrated effectiveness of developed strategies in identifying contamination origins across different stream configurations.
  • Provided practical insights for the design of robust water quality surveillance systems.
  • Highlighted limitations of current sampling approaches and potential improvements.

Conclusions:

  • The proposed sequential sampling strategies offer an optimized approach for source identification in stream networks.
  • These strategies have practical implications for environmental enforcement and toxic release management in water systems.
  • Further research can explore applications in complex systems like sewerage networks.