types of data

• what does qualitative data focus on?

  thoughts and feelings and it usually involves some form of interview or observations
• is qualitative data meaningful and detailed?

  yes
• how is qualitative data collected?


  unstructured interviews, case studies, open questionnaires, some observational studies
• how can you draw conclusions from qualitative data?

  • data needs to be categorised ( pre-existing, set before analysis) and emergent (find during analysis)
  • categories summarise the data and evidenced with quotes from actual research
• what are the strengths of how to draw conclusions from qualitative data?

  highly detailed, high validity, meaningful
• what are the weaknesses of how to draw conclusions from qualitative data?


  hard to replicate, subjective during analysis, time consuming to analyse
• quantitative data

  • less meaningful as info has a narrow focus
  • can become qualitative
• how do you collect quantitative data?

  experiments, correlations structures observations, structured interviews, closed questions
• what are the strengths of collecting quantitative data?

  easy to analyse, easy to replicate
• what are the weaknesses of collecting quantitative data?

  less meaningful, lacks ecological validity
• what are the types of data collection?

  • primary data
  • secondary data
  • meta-analysis
• what is primary data?

  researcher collects research first hand
• what are the strengths of primary data?

  researcher has control over the data, applicable and relevant to this research
• what are the weaknesses of primary data?

  very lengthy therefore very expensive (designing and recruiting ppts)
• what is secondary data?

  research that already has been collected by another researcher (for their purpose)
• what are the strengths of secondary data?

  easier and cheaper to use others data, less time consuming, such data will have been statistically tested (significance is known)
• what are the weaknesses of secondary data?

  the data may not fit the needs of the study. Data may be outdated
• what is meta-analysis?

  lots of studies with similar hypotheses are drawn together and 1 conclusion is drawn
• what are the strengths of meta-analysis?

  increases validity of conclusions, the sample is larger than the original, increases generalisability
• what are the weaknesses of meta-analysis?

  many confounding variables, sample sizes, who the sample are. researcher selects studies (so may only choose specific ones)