types of data

• qualitative data is non-numerical data expressed in words like extract from a diary
• Strength and limitation of qualitative data:

  • richness of detail- much broader in scope and quantitive data. More meaningful, great to validity
  • Difficult to analyse– hard to identify patterns and make comparisons. Leads to subject of interpretation and research a bias
• Quantitive data is numerical data like reaction time or number of mistakes
• Strengthen limitation of quantitive data:

  • Easier to analyse– control graph and touch the averages. So comparisons between groups can be made
  • Narrower in meaning– express less detail than qualitative data. Low external validity
• Primary data is firsthand data collected for the purpose of the investigation
• Strengthen limitation of firsthand data:

  • Fits the job – study designed to extract only the data needed. Information is directly relevant to research aims
  • Requires time and effort – designing and collecting questionnaires takes time and expense. Secondary data can be assessed within minutes
• Secondary data is collected by someone other than the person who is conducting the research
• Strengthen imitation of secondary data:

  • It is inexpensive – the desired information may already exist. Requires minimal effort making it inexpensive
  • Quality may be poor – information may be outdated or incomplete. Challenges the validity of any conclusions
• Meta analysis is a type of secondary data that involves combining data from a large number of studies.
• Strength and limitation of meta analysis:

  • Increases validity of conclusions – the eventual sample size is much larger than individual samples. Increase is the extent to which generalisations can be made
  • Publication bias – research is may not select all relevant studies, leaving out negative or non-significant results. Therefore conclusions mean like validity