Types of data

• Qualitative data

  Non numerical data expressed in words.
• Strength of qualitative data

  Richness in detail as it gives the respondent more of an opportunity to fully report their thoughts, meaning the data has greater external validity.
• Limitation of qualitative data

  Difficult to analyse as its hard to identify patterns which may lead to researcher bias.
• quantitative data

  Numerical data.
• Strength of quantitative data

  Easier to analyse as we can draw graphs and calculate averages so comparisons can be made.
• Limitation of quantitative data

  Less detail meaning lower external validity.
• Primary data

  ‘First-hand’ data collected for the purpose of the investigation.
• Strength of primary data

  The data fits the jobs as its specifically found for the investigation meaning to information is directly relevant to the research aims.
• Limitation of primary data

  Requires time and effort as designing and collecting takes time and expense, whereas secondary data can be assessed within minutes.
• Secondary data

  Collected by someone other than the person who is conducting the research.
• Strength of secondary data

  Inexpensive as the desired information already exists.
• Limitation of secondary data

  Quality of data may be poor as information may be outdated or incomplete, which challenges the validity of any conclusions.
• Meta-analysis

  A type of secondary data that involves combining data from a large number of studies.
• Strength of meta-analysis

  Increases the validity of conclusions meaning generalisations can be made.
• Limitation of meta-analysis

  Publication bias as researchers may not select all relevant studies, therefore conclusions may lack validity.