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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 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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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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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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Group Design02:01

Group Design

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The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
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An Unbiased Approach of Sampling TEM Sections in Neuroscience
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Sampling in Developmental Science: Situations, Shortcomings, Solutions, and Standards.

Marc H Bornstein1, Justin Jager1, Diane L Putnick1

  • 1Child and Family Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Public Health Service.

Developmental Review : DR
|January 13, 2015
PubMed
Summary

This study evaluates four developmental science sampling methods: population-based probability, convenience, quota, and homogeneous sampling. It assesses their impact on generalizability, subgroup analysis, and recruitment efficiency for better research practices.

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Area of Science:

  • Developmental science research methodologies.
  • Statistical analysis in social sciences.

Background:

  • Sampling is crucial in developmental science but often overlooked.
  • Inadequate sampling impacts study generalizability and subgroup analysis.
  • Key sampling strategies require thorough evaluation.

Purpose of the Study:

  • To describe, discuss, and evaluate four prominent sampling strategies in developmental science.
  • To assess sampling strategies based on representativeness, generalizability, recruitment costs, statistical power, and data noise.
  • To analyze the use of these strategies in leading developmental science journals.

Main Methods:

  • Evaluation of population-based probability sampling, convenience sampling, quota sampling, and homogeneous sampling.
  • Assessment criteria included representativeness of target populations and subsamples, recruitment efforts and costs, statistical power for detecting subsample differences, and handling of data noise.
  • Analysis of sample composition (gender, ethnicity, socioeconomic status) to illustrate strategy effectiveness.
  • Tallying the usage of the four sampling strategies across five major developmental science journals.

Main Results:

  • The study provides a comparative analysis of the strengths and weaknesses of each sampling strategy.
  • Findings highlight how different sampling methods affect the generalizability of findings to the broader population and specific subgroups.
  • The frequency of use for each strategy in prominent journals is documented, revealing current practices.

Conclusions:

  • Recommendations are provided for best practices in sample selection and reporting in developmental science.
  • The study emphasizes the need for careful consideration of sampling strategies to enhance research rigor and validity.
  • Promoting transparent reporting of sampling methods is essential for advancing the field.