Types of data

• Quantitative Data

  Is expressed numerically. Quantitative data collection techniques usually gather numerical data in the form of individual scores from participants such as a number of words a person was able to recall in a memory experiment. 

  Data is open to being analysed statistically and can be easily converted into graphs, charts, etc.
• Evaluation of Quantitative Data

  Strengths

  • Quantitative data is relatively simple to analyse, therefore comparisons between groups can be easily drawn. 
  • Also, data in numerical form tends to be more objective and less open to bias.
• Evaluation of Quantitative Data

  Weaknesses 

  • On the other hand, quantitative data is much narrower in meaning and detail than qualitative data. It this may fail to represent ‘real life.’
• Qualitative Data

  Is expressed in words, rather than numbers or statistics and may take the form of a written description of the thoughts, feelings and opinions of participants. 

  Thus, transcripts from interviews, diaries or notes are a form of qualitative data. 
• Evaluation of Qualitative Data

  Strengths

  • Offers a researcher more richness of detail than quantitative data. It is much broader in scope and gives the participants the opportunity to more fully report their thoughts, feelings and opinions on a given topic. 

  Qualitative data tends to have greater external validity. It provides the researcher with more meaningful insights.
• Evaluation of Qualitative Data

  Weaknesses

  • Quantitative data is often difficult to analyse. It tends not to lend itself to being summarised statistically so that patterns and comparisons within and and between data may be hard to identify.  
  • As a consequence, conclusions often rely on on the subjective interpretations of the researcher and these may be subject to bias
• Meta-analysis

  A form of research method that uses secondary data is meta-analysis. This refers to a process in which a number of studies are identified which have investigated the same aims/hypotheses. 

  It is the statistical combination of results from two or more separate studies.
• Meta-analysis

  Strengths

  • Meta-analysis allows us to create a larger, more varied sample and results can then be generalised across much larger populations, increasing validity.
• Meta-analysis

  Weaknesses

  • However, meta-analysis may be prone to publication bias, sometimes referred to as the file drawer problem. The researcher may not select all relevant studies, choosing to leave out those studies with negative or non-significant results. Therefore the conclusions can be biased.
• Primary Data

  Primary data (sometimes called field research) refers to original data that has been collected specifically for the purpose of the investigation by the researcher. It is data that arrives first-hand from the participants themselves. 

  Data that has been collected by conducting an experiment, questionnaire, interview or observation would be classed as primary data.
• Evaluation of Primary Data

  Strengths

  • Primary data is authentic data obtained from the participants themselves for the purpose of a particular investigation. Questionnaires and interviews, for instance, can be designed in such a way that they specifically target the information that the researcher requires.
• Evaluation of Primary Data

  Weaknesses

  • To produce primary data, however, requires time and effort on the part of the researcher. Conducting an experiment, for instance, requires considerable planning, preparation and resources, this is a limitation. 
• Secondary Data

  Secondary data is data that has been collected by someone other than the person who is conducting the research. In other words, this is data that already exists before the psychologist begins their research or investigation. 

  Secondary data has already been subject to statistical testing and therefore the significance is known.
• Secondary Data

  Secondary data includes data that may be located in Journal articles, books or websites.
• Evaluation of Secondary Data

  Strengths

  • Secondary data may be inexpensive and easily accessed requiring minimal effort. 
  • When examining secondary data the researcher may find that the desired information already exists and so there is no need to conduct primary data collection.
• Evaluation of Secondary Data

  Weaknesses

  • There may be substantial variation in the quality and accuracy of secondary data. Information might at first appear to be valuable and promising but, on further investigation, may be outdated or incomplete.
  • The content of the data may not match the researchers needs or objectives. This may change the validity of any conclusions.