Sampling Techniques

Discoveries in science often begin with a passive, sometimes banal, observation. The researcher then asks a question, then formulates a hypothesis. Then, the hypothesis is tested by gathering data. Data collection is a step in the scientific method of utmost importance. A haphazard collection of data can Lead to research that is biased, irreproducible or inconclusive. Therefore, research scientists rely on establishing sampling techniques.

Sampling Techniques in Research

To be able to test a hypothesis, more often than not, data is required. Good data is the foundation of a robust scientific conclusion.

Researchers have devised sampling techniques to achieve these goals, a defined procedure to obtain data from individuals within a target population.

Types of Sampling Techniques

Choosing a sampling procedure often depends on the nature of the trait being studied.

The difference between these two examples is the nature of the data being obtained. The first example is quantitative or measurable using numbers, and the second example is qualitative or measured using words, descriptions, or statements.

Qualitative Sampling Techniques

Qualitative sampling is used when wanting to collect opinions, feelings, testimonials, descriptions, or other verbal or textual statements. Qualitative sampling lends itself to non-probability sampling, which are sampling techniques where the subjects are selected from the target population and chosen subjectively by the researcher. The types of non-probability sampling are:

• Convenience Sampling

• Purposive Sampling

• Snowball Sampling

• Quota Sampling

Convenience Sampling

Convenience sampling is a method where participants are picked simply because they are the most accessible. Convenience sampling can Lead to bias, but it can nonetheless be helpful when acquiring preliminary information about a target population.

Purposive Sampling

Purposive sampling, or judgemental sampling, is a method where the researcher decides which members of the target population will be sampled. Also prone to bias, this type of sampling can efficiently filter out members of a population that a researcher may not want to sample yet. It is an excellent way to get preliminary information promptly.

Snowball Sampling

Snowball sampling, or referral sampling, is a method where the study participants may be difficult to locate or access. Sometimes the subject matter is isolated, hidden, or reluctant to speak or participate. Snowball sampling uses existing participants to find other participants. This can lead to skewed data because the sample members are, by their nature, inherently correlated.

Quota Sampling

Quota sampling is a method where volunteers who meet pre-selected criteria are sought as representatives of the target population. Bias may be introduced here because the sample members inherently have more time to participate. It may also be biased based on the researcher's chosen criteria.

Quantitative Sampling Techniques

Quantitative sampling is used when wanting to collect quantities or measurements. Quantitative sampling is best suited to probability sampling, which are techniques where the subjects selected for sampling out of the target population have been randomly chosen by an objective and replicable procedure. The types of probability sampling are:

• Simple Random Sampling
• Cluster Sampling
• Systematic Sampling
• Stratified Random Sampling

Simple Random Sampling

Simple random sampling is a method where the participants are selected haphazardly from the target population. It is genuinely unbiased but offers the researcher no way to manage which subjects get chosen, which can lead to some unnecessary voluminous or redundant sampling.

Cluster Sampling

Cluster sampling is a method where the population is separated into groups with the same characteristics. The target population then becomes that group or cluster. This type of sampling is beneficial because it pre-sorts the data.

Systematic Sampling

Systematic sampling is a sampling method where the researcher selects participants from the target population at a predefined interval.

Systematic sampling makes the assumption the population is evenly distributed. Otherwise, the population might have natural groupings that are eliminated by systematic sampling, leading to unreliable data.

Stratified Random Sampling

Stratified random sampling is a sampling method that is a combination of cluster sampling and simple random sampling. The target population is broken up into unique groups. The groups themselves are then each randomly sampled for participants. This type of sampling is useful when comparing two or more groups against each other.

Examples of Quantitative Sampling Methods

There are infinitesimal ways to count or measure an attribute. Volume, quantity, distance, weight, area, intensity, or temperature are all quantifiable characteristics. This leads to multiple ways to measure and express quantitative data. Some examples are presented here:

• Abundance scale – a method of categorising species into different abundances (e.g. DAFOR scale)

• Species richness – the number of species present

• Percentage cover – the proportion of the ground occupied by a species

• Lincoln Index – an equation used to estimate population size

• Species diversity – the variety of different species in a habitat (e.g. Shannon Diversity Index and Simpson's Index of Biodiversity)

• Species frequency – the probability of occurrence of a species

Methods

A method is a set of procedures and tools to perform a task. Specifically, the job is obtaining data. Here is a preview of the methods used in environmental studies:

• Quadrats – frames used to assess the coverage and frequency of vegetation or sessile animals. There are three types: open-frame Quadrats, grid Quadrats, and point Quadrats.

• Kick Sampling – dislodging benthic organisms for sampling using your heel.

• Surber Samplers – nets that sit on the water's surface to collect macroinvertebrates.

• Colonisation Media – a range of materials used to analyse the colonisation rate of aquatic organisms.

• Pitfall Traps – sunken traps used to collect mobile invertebrates.

• Sweep Nets – nets used to collect invertebrates living on leaves.

• Beating Trays – sheets placed below leaves to catch invertebrates disturbed using sweep nets.

• Light Traps – light sources for Trapping flying invertebrates at night.

• Tüllgren Funnel – used to extract invertebrates from the soil in the lab.

• Earthworm Extraction – removing earthworms from the soil.

Measurement of Abiotic Factors

Environmental science researchers are also interested in the abiotic factors of an ecosystem. These factors directly affect all organisms, including us. Global temperatures and carbon dioxide levels are an example of abiotic factors that are trending research topics that impact humankind. Here are commonly researched abiotic factors.

• Light intensity – a measure of brightness

• Temperature – a measure of warmth

• Wind velocity – a measure of wind speed

• Humidity – a measure of atmospheric water vapour

• Water turbidity – a measure of the cloudiness of water

• Water pH – a measure of acidity or alkalinity of water

• Water ion concentration – a measure of the water's dissolved ion content

• Soil Analysis – measurements of soil that indicate ecosystem health and species diversity

  • Texture

  • Soil pH

  • Water Content

  • Organic Matter Content

  • Bulk Density