5. Types of Data

• 1. Types of Data - Qualitative Data

  Qualitative Data - written description.

  • rich/detailed.
  • real-life settings.
  • high validity.
  • attitudes/opinions.
  • observed, not measured.
  • subjective (low reliability).
• 1a. Types of Data - Qualitative Data

  Qualitative Data - Strengths:

  • depth/detail = meaningful insight.
  • high external validity.

  Qualitative Data - Limitations:

  • complex, hard analyse.
  • can’t be summarised statistically; patterns within/between data hard to identify.
  • subjective = open to bias if researcher has (unconscious) expectations of what to find.
• 2. Types of Data - Quantitative Data

  Quantitative Data - numerical data.

  • scientific/objective.
  • statistically measured.
  • high reliability.
  • artificial setting.
  • measures of psychological variables.
  • averages/differences.
• 2a. Types of Data - Quantitative Data

  Quantitative Data - Strengths:

  • easy analysis = comparisons easily drawn.
  • objective, less open bias (high validity).
  • quick, cheap, easy obtain.

  Quantitative Data - Limitations:

  • oversimplifies reality (low external validity).
• 3. Types of Data - Primary Data

  Primary Data - collected first-hand.

  • gathered through experiment, questionaries, interview, observations.
  • qualitative/quantitive data.
• 3a. Types of Data - Primary Data

  Primary Data - Strengths:

  • authentic data.
  • researcher control, specifically target required info through things like questionnaires (higher internal validity).

  Primary Data - Limitations:

  • time-consuming, expensive.
• 4. Types of Data - Secondary Data

  Secondary Data - already existing data.

  • already had statistical testing, significance known.
  • journal articles, books, websites, gov. statistics, health report, etc.
• 4a. Types of Data - Secondary Data

  Secondary Data - Strengths:

  • quick, cheap, easily obtained.

  Secondary Data - Limitations:

  • may not fit exact needs of research (outdated/incomplete) = lower internal v.
• 5. Types of Data - Meta-Analysis

  Meta-Analysis - examine results of several previous studies.

  • gain confidence + identify possible trends.
  • produce overall statistical conclusion based on range of studies.
• 5a. Types of Data - Meta-Analysis

  Meta-Analysis - Strengths:

  • larger, more varied sample = generalised to other populations.

  Meta-Analysis - Limitations:

  • publication bias = may leave out negative results so conclusions biased bc only represents some relevant data.