Random Sampling

It is important to avoid bias and ensure the samples are representative of the whole population.

It is often impractical or impossible to measure every single individual when investigating population traits.

How random sampling works:

• Choose an area

• Ransomly generate coordinates across the area

  • This prevents sampling bias by removing human involvement in choosing samples

• Collect samples from random coordinates

  • This gives us samples that are representative of the population

• Repeat this several times

  • This gives us a large sample size and minimises teh effects of chance

• Analyse the data collected

  • This let's us identify any relationships

Random sampling techniques

Sampling animals

• Pooter

  • Samples small insects

  • Sucks air containing the into a plastic container via a tube

• Sweep net

  • Staples insects in long grass or air

  • The net is swept in a “figure of eight“ motion

• Pitfall trap

  • Samples small ground crawling animals like insects and spiders by catching them in a hidden traps

• Tree beating

  • Samples the invertebrates living in a tree or bush by shaking or beating the tree to dislodge insects onto a white sheet below.

• Kick sampling

• This samples river organisms by kicking a river bank and catching organisms downstream in a net.