Quantitative and Qualitative Data
Paper 2 Approaches to Human Behaviour
Qualitative and Quantitative Data in Psychological Research
Qualitative and Quantitative data types? When conducting psychological research, one of the first decisions that a psychologist or researcher will need to make is what type of data they wish to collect. In the most part, there are two main types of data that a psychologist can select to collect, quantitative data or qualitative data. When making a decision about the type of data that a researcher is wanting to collect, they need to consider a number of factors including; how easy the data would be to analyse, the impact of the data on the validity and reliability of the the research findings, the time in which it would take to analyse the data, the accuracy of the data once analysis has taken place etc…
In the psychology exam qualitative and quantitative data is assessed quite frequently as a ‘shorter answer question.’ questions usually center around candidates identifying the type of data that a psychologist has collected based on a given stem/case study of research or, candidates can get asked to design their own piece of research and identify/justify the type of data that they will be collecting. Additionally, candidates need to know the strengths and weaknesses associated with collecting both qualitative and quantitative data.
Quantitative Data
Quantitative data can be defined as data that is collected in numerical form (numbers and figures). Examples of quantitative data include; the number of words participants recall from a memory test, reaction times of participants on a driving simulation task, the time in minutes it takes a participant to complete an escape room etc…
Quantitative data is statistical therefore allowing researchers to calculate averages in the form of averages (measures of central tendency), how dispersed the data that has been collected is (measures of dispersion) and statistically analyse the data in order to assess whether or not the findings are significant or insignificant (inferential testing).
Evaluation of Quantitative Data (AO3)
A Strength Associated with Quantitative Data:
A major strength of using quantitative data is that, due to the fact that the data is in numerical form, it means that the data is very easy to analyse. This means that the research is able to work out averages (measures of central tendency), look at how dispersed the data is in comparison to the average score (calculate measures of dispersion) and carry out statistical tests on the data in the form of inferential statistics. Furthermore, researchers can represent their findings in graphs (e.g. bar charts, scattergrams) providing visual representations/comparisons of their research findings across different conditions. This is a strength as it means that analysis of quantitative data is objective and standardised.
A Weakness Associated with Quantitative Data:
A weakness of collecting quantitative data in psychological research is that it is very limited and reduces complex human behaviour to simple numbers and figures. For example, when carrying out mood questionnaires looking to assess levels of happiness and depression, representing mood (i.e. how happy a person is on a scale of 1 to 10) is not always appropriate. Different participants may interpret the scale in different ways (i.e. two participants rating their happiness as a ‘6’ on a happiness scale doesn’t always mean that they are experiencing the same levels of happiness). Likewise, rating complex human emotions and feelings on a scale is very reductionistic, psychological research has an aim to try and explain the mechanisms behind human feelings and behaviours, such ratings on scale in some-part tell us how participants are feeling however, they don’t explain why participants are feeling this way. This is a weakness as quantitative data can be critised for being minimalistic and inappropriately reducing complex behaviour to components that are too simplistic.
Qualitative Data
Qualitative Data can be defined as data that it is written or narrative form. Examples of qualitative data include; participant responses in an interview (whereby participants are able to give detailed responses to open ended questions asked by the researcher of research assistant), participant responses to open ended questions on a questionnaire etc…
Qualitative data collection can yield lots of detailed responses for researchers to use in the research study. Quite often, qualitative data can be more difficult to analyse in comparison to quantitative data collection and so researchers often have to use different analysis techniques in order to turn their qualitative data into a form that can be analysed statistically.
Evaluation of Qualitative Data (AO3)
A Strength Associated with Qualitative Data:
A strength associated with collecting qualitative data as part of psychological research is that fact that it yields lots of rich, detail about human behaviour. For example, when completing a mood questionnaire, participants are able to fully explore their mood and describe exactly how they feel, how they act and why they feel the way that they do. This is a strength because psychological research is always striving to fully understand human behaviour and the mechanisms driving human behaviour, Gaining such insightful details from participants allows researchers to fully investigate their research aims and gain a thorough understanding of human behaviour.
A Weakness Associated with Qualitative Data:
A weakness associated with the collection of qualitative data in psychological research is the difficulties it creates when wanting to objectively analyse the results obtained. Qualitative data is highly detailed however, due to the fact that it isn’t in numerical form, it can be very difficult for researchers to analyse. Quite often, researchers want to turn the qualitative data that they have collected in quantitative data using qualitative data analysis techniques like content analysis and thematic analysis. Using these processes to analysis the qualitative data can often cause the data to loose its detail and ‘richness’ once again, reducing complex human behaviours to simple numbers and figures. Furthermore, qualitative data analysis involves sorting rich, written data into simplistic categories which can often be implicated by experimenter/investigator effects (e.g. the experimenters may interpret the participant’s response to mean something that the participant hadn’t intended to mean). This is a weakness because the process of analysing qualitative data can be seen to be subjective. Subjective analysis processes can affect the overall validity of the participant responses/overall research and may mean that researchers/experimenters are not measuring what they are intending to measure.