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Related Concept Videos

Sampling Methods: Overview01:06

Sampling Methods: Overview

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 sampling...
Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

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...
Sampling Theorem01:15

Sampling Theorem

In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
Sampling Plans01:23

Sampling Plans

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...
Convenience Sampling Method00:55

Convenience Sampling Method

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...
Random Sampling Method01:09

Random Sampling Method

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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Related Experiment Video

Updated: May 26, 2026

An Unbiased Approach of Sampling TEM Sections in Neuroscience
10:56

An Unbiased Approach of Sampling TEM Sections in Neuroscience

Published on: April 13, 2019

On the subject of sampling . . .

T R Konrad, G H Defriese

    American Journal of Health Promotion : AJHP
    |December 23, 2011
    PubMed
    Summary

    Sampling is crucial for program evaluation, ensuring results are generalizable and replicable. Understanding sampling principles simplifies planning and enhances the scientific rigor of evaluations.

    Area of Science:

    • Program Evaluation
    • Research Methodology

    Background:

    • Sampling often causes confusion and anxiety in program evaluation.
    • Effective sampling is essential for robust evaluation design.

    Purpose of the Study:

    • To provide practical guidelines for determining sample size in program evaluations.
    • To demystify sampling as a core component of evaluation science.

    Main Methods:

    • Focuses on principles for determining the number of participants or components for evaluation.
    • Does not detail specific sample selection techniques, referencing other sources.

    Main Results:

    • Sampling is a straightforward yet essential aspect of program evaluation.
    • Early consideration of sampling enhances generalizability and replicability.

    More Related Videos

    Sampling Soils in a Heterogeneous Research Plot
    07:11

    Sampling Soils in a Heterogeneous Research Plot

    Published on: January 7, 2019

    Related Experiment Videos

    Last Updated: May 26, 2026

    An Unbiased Approach of Sampling TEM Sections in Neuroscience
    10:56

    An Unbiased Approach of Sampling TEM Sections in Neuroscience

    Published on: April 13, 2019

    Sampling Soils in a Heterogeneous Research Plot
    07:11

    Sampling Soils in a Heterogeneous Research Plot

    Published on: January 7, 2019

    Conclusions:

    • Sound program planning must incorporate sampling considerations.
    • Practical guidance on sampling strengthens evaluation outcomes.