Types of data

• Qualitative data


  Written, non-numerical description

  Eg a diary
• Qualitative data - strengths

  • Rich in detail
  • Greater external validity
• Qualitative data - weaknesses

  • Difficult to analyse
  • May be biased
• Quantitative data


  Expressed numerically

  Eg graphs
• Quantitative data - strengths

  • easy to analyse
  • Less biased
• Quantitative data - weaknesses

  • Narrower in meaning - low external validity
• Primary data 


  collected First hand for the purpose of investigation

  ‘Field research’

  Eg from interviews
• Primary data - strengths

  • Fits the job
  • Targets relevant info - authentic data
• Primary data - weaknesses

  • Requires time and effort - eg planning an experiment
• Secondary data


  collected by someone other than the researcher

  ‘desk research’

  data already exists

  eg gov records
• Secondary data - strengths

  • Inexpensive
  • Easy to access
• Secondary data - weaknesses

  • Variation in quality - eg outdated - may not match needs
• Meta-analysis is a statistical analysis that combines the results of multiple studies to produce a single estimate of the effect size which can provide an overall conclusion ​
• Meta-analysis - strengths

  • High validity/ high validity of conclusions
• Meta-analysis - weaknesses

  • Prone to publication bias (file-drawer problem)