types of data

• quantitative data

  This is data expressed numerically.
• evaluations - quantitative data

  strength(s):

  -easier to produce than qualitative data.

  -data is objective, people cannot interpret it differently.

  
  

  weakness(es):

  -less detailed, it does not give a good explanation to why the finding are what they are.
• qualitative data

  This is data expressed in words.
• evaluations - qualitative data

  strength(s):

  -more detailed than quantitative data, provides a better explanation.

  
  

  weakness(es):

  -can take longer to produce than quantitative data - this can mean data might be subjective.

  -people will interpret the data differently.
• meta-analysis

  A specific form of secondary data that combines the findings of multiple studies on a particular topic. This can make a joint conclusion and enable an effect size to be calculated.
• evaluations - meta-analysis

  strength(s):

  -larger, more varied sample - findings can be generalised as the sample is more representative.

  
  

  weakness(es):

  -publication bias. Articles that find a significant difference in data are more likely to be published - file-drawer problem; lower validity.
• primary data

  This is original data - it comes from the researcher themselves.
• evaluations - primary data

  strength(s):

  -there is high validity as the research is collected purposefully for the study.

  
  

  weakness(es):

  -it takes a lot of time and money to get. Secondary data is easier to use.
• secondary data

  This is data that someone else has collected but we use to support our research.
• evaluations - secondary data

  strength(s):

  -anyone can access secondary data; it is easy to get hold of.

  
  

  weakness(es):

  -there is low validity. There could be researcher and publication bias as well as extraneous variables we are not aware of.
• nominal data

  data is separated into categories.
• ordinal data

  data is put in order.
• interval data

  data is measured using units of equal intervals.