Types of data

• Primary data= data that has been obtained first hand by a researcher from participants for the purpose of their study- can be from an experiment, self-report technique or observation.
• Primary Data Evaluation:

  • Strength- the researcher has lots of control over the nature of the data used, which can ensure accuracy.
  • Weakness- data collection can be costly in terms of time & resources.
• Secondary data= data that has been collected by someone else at a time before the current researcher begins their study, for different purposes. It may have been subjected to statistical analysis, therefore significance is known & research can be found in articles, books, government data (census) etc.
• Secondary Data Evaluation:

  • Strength- easier, simpler & cheaper to just use someone else's data than collect your own.
  • Strength- in many cases we already know the data being used is significant; already been checked & validated- worthy of publication.
  • Weakness- the data may not fit the needs of the study.
  • Weakness- no control over methods of data collection.
• Meta Analysis:

  • Is a research method that solely uses secondary data.
  • It reviews existing data from multiple studies with the same/ similar aims/ hypotheses.
  • Provides an overall "effect size" as the DV- this is a statistical analysis that means overall trends in data are assessed & a conclusion is made based on all of that data, in terms of the strength of the difference or relationship being assessed.
• Meta Analysis Evaluation:

  • Strength- increasing the sample size from which conclusions are drawn, can increase generalisability & therefore validity.
  • Strength- can allow us to see an overall trend if lots of studies have been contradictory.
  • Weakness- research designs vary greatly, so actually the research that is 'lumped together' as having the same aim may not actually be comparable, so conclusions may not be valid.
• Quantitative research= data in a measurable numeric form.
• Quantitative Research Evaluation:

  • Strength- can be analysed more easily.
  • Strength- can be summarised into graphs & tables.
  • Weakness- oversimplifies human experience as behaviour is explained in a numerical form, therefore loses validity.
  • Weakness- only tells us how often a behaviour happens & not the reasons why.
• Qualitative research= data that is non-numerical, eg speech, pictures, books, videos.
• Qualitative Research Evaluation:

  • Strength- gives in-depth information which represents the true complexity of humans.
  • Strength- can give us the reasons behind a behaviour.
  • Weakness- difficult to analyse & summarise the data.
  • Weakness- can be subjective; it's affected by the researcher's personal expectations.