Types of data

• Quantitive data is data in the form of numbers, can be transformed into tables, graphs, charts, percentages, fractions. They are statistically analysed using: mean, mode, range and inferential statistics
• Quantitve data generally generated through research methods such as: experiments, observations, correlations and questionnaires
• Strengths of Quantitve data:

  • mostly reliable as easy to analyse and compare
  • techniques used to collect it tend to be replicable- standardised procedures, correlational analysis, meta- analysis
  • tends to highlight trends and patterns which are useful and applicable to general laws of behaviour
• Limitations of quantitative data:

  • not able to reveal the reason behind the behaviour, only what it is, not why
  • lacking in explanatory power- lowers the validity
  • over- simplify the complex nature of human behaviour and experience
  • limited usefulness
• Qualitative data is data in the form of words or images- thoughts and feelings expressed
• Qualitative research methods include: interviews, diary entries, naturalistic observations and open- ended questions- can be analysed using content analysis or thematic analysis
• Strengths of qualitative data:

  • allows researcher to gain insight into the nature of individual experience and meaning
  • higher in ecological validity
  • can be used to deepen knowledge of complex behaviours
• Limitations of qualitative data:

  • difficult to generalise as tend to be found in smaller sample sizes
  • subjective nature of quantitative method does not have scientific rigour (lack of objectivity and control)
  • lacking in reliability
• Primary data refers specially to the research aim and is collected at the source, from condition 1 and 2, after running an experiment. It is not previously published research
• Strengths of primary data:

  • more reliable and valid as researcher has full control over how data is collected
  • may be more trustworthy as researcher is aware research ill be subjected to peer review: if negative would damage their reputation, thus would take care to present best design study
• Limitations of primary data:

  • derived from a single study meaning it has limited statistical power
  • expensive
  • time- consuming
• Secondary data is data that has been obtained by other researchers who have been working towards their own specific hypothesis- data already pre- existing: allowing non-interested researcher to gain clear overview of the topic
• Strengths of secondary data:

  • already peer reviewed meaning there is confidence in the data
  • time and money not wasted
  • new insight into existing theories and research
• Limitations of secondary data:

  • may not directly address the aims or the hypothesis of the research
  • researcher has a lack of familiarity with the data- could misinterpret some aspects of the original research: affects validity of research
  • do not know the control and rigour of the OG researcher- lack of reliability of the data