Sampling Methods

Sampling methods are something most of us seem to have forgotten about from last year (it probably wouldn't do you any harm to dig out you green skills booklet from last year!) but it is important that we mention them in our methodology. So what excatly are they and why do we need/use them???

SAMPLING = A means of collecting data that is representative of a particular issue or subject area without actually having to record every bit of data
--->All data collection operates within a number of constraints, although particularly the area that has been selected fro studt and the time that is available for data collection. Whilst in some circumstances sampling is necessary, using sampling means it is possible to save time and money without jeopardising the quality of the data that is collected.

Avoiding Bias.....
 - When deciding how to take a sample and how many samples to take the main consideration is obtaining representative results = avoiding bias
- Bias can be caused by many things such as not taking enough samples or collecting the data at the wrong time or by chossing the wrong method in order to decide who/what you will sample

Sampling Methods.....
Point Sampling :- Involves choosing individual points and sampling at this points, such as specific houses down a street
Line Sampling :- Involves taking measurements along a line, for example to sample vegetation across sand dunes you may lay a tape across the dune
Random Sampling :- Sampling using random numbers, where each item in the parent population must have an equal chance of being selected for the sample
Advantages:
        - Removes human bias involved in the selection process
Disadvantages:
        - If sample size is quite small you might obtain an unrepresentative result
        - Access may be an issue
Stratified Sampling :- Deliberately choosing which bits to sample - usually to ensure coverage of all areas you want to study, based on prior knowledge.
Advantages:
        - Avoids bias that can arise from random and systematic sampling as ensures that each group is fairly represented
        - Ensures all areas are covered
Disadvantages:
        - Difficult to know excatly which subsets of data you want to include
        - Access may be a problem
        - Requires good prior knowledge of an area
Systematic Sampling :- Data is collected at a set interval, such as every fifth house or every 5 metres
Advantages:
        - Quicker, easiers and more convenient to carry out than random sampling and can be more accurate because avoids the remote possibility that the random sample selects too many examples from one part of the distribution
        - Ensures good coverage of an area
        - Accurately reflects continous changes in variables
Disadvantages:
        - Can inadvertently pick up bias, e.g sampling every 50 metres along a beach may also coincide with location of groynes
        - May exclude key sites
Pragmatic Sampling :- Based on practical reasons, for example you cannot trespass on peoples property and would not sample sediment in a deep fast flowing river

Combining Sampling Methods.......
It is possible to combine some of the sampling methods during a fieldwork investigation and this is often the best thing to do so, as an example if you were to plan a questionnaire for Poole, you could use startified sampling to ensure that various age/gender groups are included within but use systematic sampling to decide who precisely to ask, such as every 5th person. Whilst you would probably use a combination of stratified and pragmatic to decide on the location for your questionnaire.