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Sampling Plans

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...

Sampling Methods: Sample Types

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 Methods: Overview

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...

Systematic Sampling Method

Systematic 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.
Systematic sampling is one of the simplest methods...

Sampling Distribution

Sampling Distribution

Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...

Environmental Applications of Microorganisms

Environmental Applications of Microorganisms

Microorganisms play a pivotal role in maintaining ecosystem balance by recycling essential elements such as carbon, nitrogen, and phosphorus, as well as supporting processes like bioremediation, wastewater treatment, and biofuel production.Microbes in Elemental CyclesIn the carbon cycle, microorganisms decompose organic matter, releasing carbon dioxide via aerobic respiration. This carbon dioxide is subsequently used by photosynthetic organisms to synthesize organic compounds, closing the...

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Related Experiment Video

Updated: May 9, 2026

Methods of Soil Resampling to Monitor Changes in the Chemical Concentrations of Forest Soils

Methods of Soil Resampling to Monitor Changes in the Chemical Concentrations of Forest Soils

Published on: November 25, 2016

BAS: balanced acceptance sampling of natural resources.

B L Robertson¹, J A Brown, T McDonald

¹Department of Mathematics and Statistics, University of Canterbury, Private Bag 4800, Christchurch, New Zealand.

|July 13, 2013

Summary

Designing efficient natural resource surveys requires spatially balanced sampling. This study introduces balanced acceptance sampling (BAS), a faster and simpler method ensuring even sample distribution for improved monitoring efficiency.

Keywords:

Environmental sampling Halton sequence Spatially balanced sampling Unequal probability sampling

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Deployment and Retrieval of Mineral Samplers

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Published on: January 20, 2026

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Last Updated: May 9, 2026

Methods of Soil Resampling to Monitor Changes in the Chemical Concentrations of Forest Soils

Methods of Soil Resampling to Monitor Changes in the Chemical Concentrations of Forest Soils

Published on: November 25, 2016

Deployment and Retrieval of Mineral Samplers

Deployment and Retrieval of Mineral Samplers

Published on: January 20, 2026

Area of Science:

Ecology
Environmental Science
Statistical Modeling

Background:

Efficient natural resource surveys depend on understanding resource spatial distribution.
Spatially balanced sample designs are generally more efficient than non-balanced designs.
Even distribution of samples across the resource extent is key to spatial balance.

Purpose of the Study:

To introduce a novel spatially balanced sampling design.
To provide a method applicable to discrete and continuous populations in multi-dimensional space.
To offer a conceptually simpler and faster alternative to existing designs.

Main Methods:

Developed a new sampling design termed balanced acceptance sampling (BAS).
Utilized the Halton sequence to ensure spatial diversity of selected locations.
Employed acceptance sampling to achieve targeted inclusion probabilities.

Main Results:

The BAS design demonstrates superior spatial balance compared to competing methods.
BAS executes faster and is conceptually simpler than existing spatially balanced designs.
The algorithm is implemented in a freely available R package.

Conclusions:

Balanced acceptance sampling (BAS) offers an efficient and effective approach for natural resource surveys.
The BAS design enhances monitoring programs through improved spatial distribution of samples.
The availability of the BAS algorithm in an R package facilitates its practical application.