Sampling Techniques
What is sampling?
A shortcut method for investigating a whole population
Data is gathered on a small part of the whole parent population or sampling frame, and used to inform what the whole picture is like
Why sample?
In reality there is simply not enough time, energy, money, labour or man power, equipment, access to suitable sites to measure every single item or site within the parent population or whole sampling frame. Therefore an appropriate sampling strategy is adopted to obtain a representative, and statistically valid sample of the whole.
Sampling considerations
Larger sample sizes are more accurate representations of the whole
The sample size chosen is a balance between obtaining a statistically valid representation, and the time, energy, money, labour, equipment and access available
A sampling strategy made with the minimum of bias is the most statistically valid
Most approaches assume that the parent population has a normal distribution where most items or individuals clustered close to the mean, with few extremes
A 95% probability or confidence level is usually assumed, for example 95% of items or individuals will be within plus or minus two standard deviations from the mean
This also means that up to five per cent may lie outside of this - sampling, no matter how good can only ever be claimed to be a very close estimate
