Fieldwork

• primary data = data you collect yourself
• secondary data = data someone else published that you use
• quantitative data = involves data, numbers and counting
• qualitative data: non-numerical, subjective, adds meaning/understanding
• sample size:

  • more measurements/surveys you get the more reliable your data
  • time consuming to do on your own
• survey locations/sites: where will the data be collected, how will you decide this
• accuracy:

  • how can you ensure the data is accurate
  • equipment used, taking several samples and calculating an average
• reliability and accuracy of data:

  • sample size
  • survey locations/sizes
  • accuracy
• types of sampling:

  • opportunity
  • random
  • stratified
  • systematic
• opportunity sampling = no system, easiest to access
• random sampling = chosen at random so every pebble/person has an equal chance of being selected (random number generator)
• stratified sampling = deliberately introducing bias so that the data is representative of the whole population and everything/everyone is included
• systematic sampling: working to a system to collect data, data is collected at regular intervals
• advantages of random sampling:

  • can be used with large sample populations
  • avoid bias
• disadvantages of random sampling:

  • can lead to poor representations of the overall parent population or area if large areas are not hit by the random numbers generwted
  • this is made worse if the study area is large
  • may be practical constraints in terms of time and access to areas
• systematic sampling advantages:

  • good coverage of study areas can be more easily achieved than using random sampling
  • more straight-forward than random sampling
• systematic sampling disadvantages:

  • more biased as not all members or points have an equal chance of being selected
  • may lead to over or under representation of a particular pattern
• stratified sampling advantages:

  • size of sub-groups are known, can generate results which are very representative of the whole population
  • correlations and comparisons can be made between sub-groups
• stratified sampling disadvantages:

  • size of sub-groups must be known accurately to be able to work
  • may be difficult to ask people certain questions
  • depending on the time of day certain groups of people may not be prsent