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.
Good data is accurate, comprehensive, relevant, credible, unbiased, accessible and ethically obtained.
Researchers have devised sampling techniques to achieve these goals, a defined procedure to obtain data from individuals within a target population.
Population: A convergence of subjects with similar characteristics interacting with other populations in the same geographic region.
Target Population: The isolated population(s) being observed or measured for data gathering.
Sample: A subgroup of a population used for observation to be representative of the whole population.
Sampling Technique: A defined procedure to obtain samples and data from a target population.
Types of Sampling Techniques
Choosing a sampling procedure often depends on the nature of the trait being studied.
An inquiry may seek information about the height of a tree population, whereas another study may inquire about the feelings people experience when seeing a sunset.
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.
For example, the participants could be grouped by age, height, or location.
Systematic Sampling
Systematic sampling is a sampling method where the researcher selects participants from the target population at a predefined interval.
For example, a researcher may assign a unique number to every apple orchard tree and select one out of every five.
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
Sampling Techniques - Key takeaways
A sampling technique is a defined procedure to obtain samples and data from a target population.
Qualitative sampling techniques include convenience, purposive, snowball, and quota.
There are quantitative sampling techniques such as simple random sampling, cluster sampling, systematic sampling and stratified random sampling.
Biotic factors, such as abundance, species richness, species diversity, species frequency, and the Lincoln index, are sampled using quadrats, surbers, kick-sampling, pitfall and light traps, sweep nets, or Tullgren funnels.
Abiotic factors, such as light intensity, temperature, wind velocity, humidity, pH, and soil texture, are often also routinely sampled to study their effect on a target population.
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