Types of data

• Official statistics

  • Quantitative numerical data collected by the government
  • Provide a wealth of data that is usually hard to access
  • High reliability
  • High representativeness
  • May define terms differently
  • Lack validity according to interpretivists
• Unofficial statistics

  • Quantitative data collected by non-governmental sources
  • Representative and reliable
  • Not standardised- might lack reliability
• Personal documents

  • Qualitative personal documents such as letters, diaries, and photographs
  • Gives a broader insight
  • Detailed- raises validity according to interpretivists
  • Difficult to make comparisons- lowers reliability
  • Low in representativeness
• Content analysis

  • Systematically studying the content of documents or media and providing qualitative and quantitative data
  • Practical and cheap
  • Can provide large scale, representative research
  • Can be longitudinal
  • Reliable as results can be cross-checked
  • Time consuming
  • Risk of subjectivity
• Longitudinal studies

  • Conducted over a long period of time, same sample visited more than once
  • Expensive and time consuming - very helpful as secondary data
  • High validity and representativeness as it provides more than a snapshot. Small samples lower representativeness in terms of sample size and diversity
  • Low reliability
• Two types of longitudinal studies

  Panel = sample is the focus of data collection at least twice and the data is collected from types of case within a panel study framework, such as people, households, schools, etc.

  Cohort = the focus of data collection is an entire cohort or a random sample of them and the cohort is made up of people who share a certain characteristic.