13. types of data

what are the types of data

1. qualitative

2. quantitative

3. primary

4. secondary

qualitative

data that is expressed in words and non-numerical

• eg interview transcript, notes recorded within a counselling session, unstructured observation

quantitative

data that can be counted, usually given as numbers

• eg data from experiments

overlaps between the two

• researchers collecting quantitative data as part of an experiment may often interview participants as a way of gaining more qualitative insight into their experience of the investigation

• similarly, there are a no. ways in which qualitative information can be converted to numerical data

qualitative evaluation

• more rich in detail as is a much broader scope and gives the participant the chance to more fully report their thoughts, feelings and opinions - greater external validity with more insight to worldview

• often difficult to analyse as tends to not lend itself to being summarised statistically so that patterns and comparisons within and between data may be hard to identify - conclusions rely on subjective interpretations

quantitative evaluation

opposite of qualitative evaluation

• data tends to be more objective and less open to bias

• narrower in meaning and detail thus may fail to represent real life

primary data

• information that has been obtained first hand by a researcher for the purposes of a research project

• data is often gathered directly from participants as part of an experiment, self report or observation

secondary data

• information that has already been collected by someone else and so pre-dates the current research project

• such data may include the work of other psychologists, journal articles or government statistics

primary evaluation

• authentic data obtained from the participants themselves for the purpose of a particular investigation - eg questionnaires/interviews can be designed in a way that they specifically target the information the researcher requires

• requires time and effort on the part of the researcher - eg conducting an experiment requires considerable planning, prep and resources which is a limitation contrasted to secondary data that can be accessed within a matter of minutes

secondary data

• may be inexpensive and easily accessed requiring minimal effort

• may be sustainable variation in the quality and accuracy of secondary data - may be outdated or incomplete and the content may not quite match the researcher’s needs or objectives, challenging conclusion validity

meta analysis

• a process in which a number of studies are identified which have investigated the same aims/hypothesis

• results can be pooled together and a joint conclusion produced

• it is possible to perform a statistical analysis and calculate an effect size giving an overall statistical measure of difference or relationship between variables across a number of studies

meta analysis evaluation

• allows the creation of a larger, more varied sample and results can then be generalised across much larger populations, increasing validity

• prone to publication bias (file drawer problem) meaning the researcher may not select all relevant studies, choosing to leave out those with negative or non significant results - thus conclusions will be biased as they only represent some of the relevant data