Data analysis: Kinds of data

• Qualitative data

  Expressed in words and may take the form of a written description of the thoughts, feelings and opinions of ppts
• Strengths of qualitative data

  Offers much more richness and much broader scope giving ppts more licence to develop their thoughts,feelings and opinions on a given subject. Has greater external validity
• Weaknesses of qualitative data

  difficult to analyse and to compare people or groups. Conclusions often rely on subjective interpretations of the researcher and these may be subject to bias
• Quantitative data

  Expressed numerically. Data open to be analysed statistically and can be easily converted into graphs/charts
• Strengths to quantitative data

  Simple to analyse and thus, comparisons between groups can be easily drawn. Data in numerical form tends to be more objective and less open to bias
• Weaknesses to quantitative data

  Much narrower in scope and meaning than qualitative data. May fail to represent 'real-life' - lack of ecological validity
• Primary data

  Refers to original data that has been collected specifically for the purpose of the investigation by the researcher: firsthand data
• Strength to primary data

  Fits the job - study designed to extract only the data needed and information is directly relevant to research aims
• Weakness to primary data

  requires time and effort and conducting an exp takes planning, preparation and resources
• Secondary data

  Data collected by someone other than the person conducting the research
• Strengths to secondary data

  Inexpensive and easily accessed requiring minimal effort. Researcher can find the desired information and there is no need to conduct primary data collection
• Weaknesses to secondary data

  Substantial variation in the quality and accuracy of secondary data. Information could be incomplete/outdated and content of data may not apply to researcher's needs