types of sampling Flashcards
what is sampling?
Sampling means taking measurements of a limited number of individual organisms present in a particular area.
Sampling can be used to estimate the number of organisms in an area without having to count them all. The number of individuals of a
ling in a
species present in an area is known as the abundance of the organism.
Sampling can also be used to measure a particular characteristic of an organism. For example, you cannot reliably determine the height of wheat by measuring one wheat plant in a farmer’s field. However, if you measure the height of a number of plants and then calculate an average, your result is likely to be close to the average height of the entire crop.
After measuring a sample, you can use the results of the sample to make generalisations or estimates about the number of organisms, distribution of species or measured characteristic throughout the entire habitat.
Sampling can be done in two ways - random and non-random.
random sampling
Random sampling means selecting individuals by chance. In a random sample, each individual in the population has an equal likelihood of selection, rather like picking names out of a hat.
To decide which organisms to study, random number tables or computers can be used. You have no involvement in deciding which organisms to investigate. For example, to take a random sample at a grass verge you could follow these steps:
1)Mark out a grid on the grass using two tape measures laid at right angles.
2)Use random numbers to determine the x coordinate and the y coordinate on your grid.
3)Take a sample at each of the coordinate pairs generated.
non-random sampling
Non-random sampling is an alternative sampling method where the sample is not chosen at random. It can be divided into three main techniques:
Opportunistic - this is the weakest form of sampling as it may not be representative of the population. Opportunistic sampling uses organisms that are conveniently available.
Stratified - some populations can be divided into a number of strata (sub-groups) based on a particular characteristic.
For instance, the population might be separated into males and females. A random sample is then taken from each of these strata proportional to its size.
Systematic - in systematic sampling different areas within an overall habitat are identified, which are then sampled separately.
For example, systematic sampling may be used to study how plant species change as you move inland from the sea. Systematic sampling is often carried out using a line or a belt transect. A line transect involves marking a line along the ground between two poles and taking samples at specified points, this can include describing all of the organisms which touch the line or distances of samples from the line. A belt transect provides more information; two parallel lines are marked, and samples are taken of the area between the two lines.
reliability
A sample is never entirely representative of the organisms present in a habitat. This may be due to the following:
Sampling bias - the selection process may be biased. This may be by accident, or may occur deliberately. For example, you may choose to sample a particular area that has more flowers because it looks interesting. The effects of sampling bias can be reduced using random sampling, where human involvement in choosing the samples is removed.
Chance - the organisms selected may, by chance, not be representative of the whole population. For example, a sample of five worms collected in a trap may be the five longest in the habitat. Chance can never be completely removed from the process, but its effect can be minimised by using a large sample size. The greater the number of individuals studied, the lower the probability that chance will influence the result. Therefore the larger the sample size, the more reliable the result.
