Types of data

Types of data

1. quantitative & qualitative data

   • quantitative data
     • measures behaviour numerically
     • can be collected from the DV in an experiment or closed questions in interviews & questionnaires
   • qualitative data
     • is non-numerical data e.g. words, pictures or videos
     • comes from : open questions, descriptions of behaviour & collected material such as articles, books, photos, web forum discussions
     • can be turned into quantitative data by tallying behavioural categories in an observation study or coding categories in a content analysis
   • qualitative & quantitative data can both be used to explore people's thoughts & feeliings

2. primary & secondary data

   • primary data
     • is collected directly, first- hand by the researcher , specifically to address the aims & hypothesis of study
     • can be collected using a research method e.g. an experiment, observation or questionnaire
     • researcher designs the study, recruits & tests participants, analyses data & draws conclusions
   • secondary data
     • is info gathered for a different purpose or another researcher, could include government statistics or health records
     • used in review studies & meta-analyses & often in correlational studies

3. Evaluation

   • quantitative data is easy to analyse
     • using descriptive statistics & statistical tests
     • but this may oversimplify reality
     • leading to meaningless conclusions
   • qualitative data provides...
     • rich, descriptive details of participants' experiences
     • this can produce unexpected insights into thoughts & behaviour
     • but this makes it harder to analyse qualitative data & draw conclusions
   • primary data collected specifically to meet aims & hypothesis of study
     • means that the researcher has high control over type, quality & quantity of data collected
     • but data collection is time consuming & often expensive
     • so studies must be very carefully designed & carried out to ensure useful data is collected
   • secondary data is simpler to access
     • if statistical tests have already been carried out the researcher knows the findings are significant
     • but variables may have been differently operationalised or procedures may vary
     • this means that secondary data may not fit needs of a new study or may not be valid for comparison with similar data from other studies