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Related Concept Videos

Sampling Methods: Overview01:06

Sampling Methods: Overview

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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. 
In analytical chemistry, the choice of...
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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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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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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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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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Systematic Sampling Method01:17

Systematic 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.
Systematic sampling is one of the simplest methods...
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Related Experiment Video

Updated: Dec 6, 2025

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
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On Senders's Models of Visual Sampling Behavior.

Y B Eisma1, P A Hancock2, J C F de Winter1

  • 1Delft University of Technology, Netherlands.

Human Factors
|October 7, 2020
PubMed
Summary

John Senders's visual sampling models demonstrate a linear relationship between signal bandwidth and sampling rate. These models, including the periodic sampling model (PSM), random constrained sampling model (RCM), and conditional sampling model (CSM), remain highly relevant.

Keywords:
bandwidthcomputer simulationreplicationsamplingvisual attention

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Area of Science:

  • Human Factors and Ergonomics (HF/E)
  • Visual Perception
  • Information Processing

Background:

  • John Senders significantly contributed to human factors/ergonomics (HF/E), particularly in visual attention.
  • This review focuses on the foundational visual sampling models from Senders's doctoral thesis.

Approach:

  • The study presents, clarifies, and expands upon Senders's visual sampling models.
  • Computer simulations and visual illustrations are employed to explicate the models.
  • A recent replication study using modern eye-tracking data validates Senders's original findings.

Key Points:

  • Senders's work established a linear relationship between signal bandwidth and visual sampling rate.
  • The core models discussed are the periodic sampling model (PSM), random constrained sampling model (RCM), and conditional sampling model (CSM).
  • Replication studies confirm the robustness and replicability of Senders's findings with contemporary technology.

Conclusions:

  • Senders's visual sampling models are enduring and continue to be relevant and applicable.
  • These models offer valuable insights for researchers and practitioners in HF/E and related fields.
  • The study encourages broader adoption and application of Senders's foundational work.