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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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Convenience Sampling Method00:55

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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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Surveys02:16

Surveys

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Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
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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 Soils in a Heterogeneous Research Plot
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Large-scale community study reveals information sampling drives fairness decisions.

Sarah Vahed1, Alan G Sanfey2,3

  • 1Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands. sarah.vahed@donders.ru.nl.

Communications Psychology
|November 27, 2025
PubMed
Summary
This summary is machine-generated.

People demonstrate fairness norms even outside the lab. In a museum Ultimatum Game (UG), participants rejected unfair offers and used proposer history to inform decisions, showing real-world inequality aversion.

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Area of Science:

  • Behavioral Economics
  • Social Psychology
  • Citizen Science

Background:

  • Empirical understanding of fairness often relies on lab studies with limited generalizability.
  • Ecological validity of fairness research is challenged by homogeneous samples.

Purpose of the Study:

  • To investigate fairness norms in a real-world, ecologically valid setting.
  • To examine decision-making in the Ultimatum Game (UG) using a citizen science approach.
  • To explore the impact of proposer history on fairness judgments.

Main Methods:

  • Embedded the Ultimatum Game (UG) in a museum setting over 13 months.
  • Collected >18,672 decisions from a heterogeneous public sample.
  • Included an option for participants to view proposer history before deciding.

Main Results:

  • Replicated classic UG findings: unfair offers were frequently rejected, confirming inequality aversion.
  • Majority of participants utilized proposer history information.
  • Information sampling heightened sensitivity to fairness violations, especially from previously generous proposers.

Conclusions:

  • Fairness norms and inequality aversion extend beyond laboratory settings.
  • Information seeking about past behavior significantly influences judgments of fairness.
  • The lab-in-the-field approach offers a scalable model for studying authentic decision-making.