1. Qualitative and Quantitative Data
How Science Works
Qualitative and Quantitative Data

2. Quantitative data
numerical data: generated by counting up the number of people who have responded in a certain way
analysed using statistics ....
Percentages: 45% of British Asian females aged said they had been subjected to racist verbal abuse in the street
Central tendency (averages) women tended to have less authoritarian personalities than men (mean for women: 45/70, men 52/70)
Measures of dispersion (variation within the scores) women tended to show greater variability than men in terms of the how authoritarian they were: (standard deviation = 2.3 for women and only 1.2 for men)
Displayed using graphs and charts (histograms, bar charts, box and whisker plots etc)
Quantitative data can also be generated from completing a ‘content analysis’ on qualitative data gathered through an interview for example.
to the transcript of the interview
count up the number of times certain themes or key words are mentioned.
e.g. of the 14 female British Asians interviewed 100% said they felt ‘unwelcome’, 70% said they felt ‘terrified’ , 89% said they had felt ‘threatened’, and 15% said they had been made to feel ‘worthless’.

3. Strengths of Quantitative
Replication and reliability
data is gathered in a structured and controlled manner: should be possible to replicate by using the same standardised procedure, instructions and questions
should be possible to replicate studies which collect quantitative data and thus check for reliability (consistency).
Quick and easy analysis
easy and quick to analyse using measures of central tendency and dispersion, and a range of graphs and charts
tables and graphs can be easily communicated to others.

4. Weaknesses of Quantitative Data
Validity
fixed response questions can lead to invalid responses which do not effectively describe the experience of the participants
Need a comprehensive pilot study; allows the researcher to ensure that the alternative answers provided suit a wide range of possible responses from the final sample.
When participants simply have to tick boxes it is very easy for them to become disinterested and disengaged from what they are doing
response set: ticking the same answer time after time when questions follow a similar format (i.e. circling a number) or they may even simply tick answers which don’t really apply to them
they are investing little in answering the questions and therefore may be less inclined to answer them properly

5. Qualitative data
in the form of words rather than numbers and involves ideas, opinions and attitudes
often ‘tells a story’.
can be collected through asking open ended questions as in an interview or questionnaire
analysed by generating themes; this can be done by carefully transcribing every word and then arranging quotes into categories; these categories and themes and then turned into models or flow charts to show links and relationships between themes (grounded theory)
Often two or more researchers independently analyse the data; their interpretations are compared and the higher the degree of similarity between their analyses, the higher the reliability of the findings and conclusions.

6. Strengths of Qualitative Data
Validity
rich source of data; participants are allowed to describe how they think or feel in their own words
not constrained by the expectations of the researchers which can sometimes be the case in fixed response questions.
New ideas
allows researchers to capture new ideas that they were not previously aware of
new information can be used to create more scientific and objective studies with higher validity
researcher gains more in-depth working knowledge of the topic area having worked with participants who have fully explained their experiences.

7. Weaknesses Qualitative Data
Validity
difficult to gather detailed qualitative data as participants often don’t want to give detailed answers
compounded by the fact that some participants may find it more difficult to express their thoughts and feelings verbally in writing or orally
wide range of reasons, including cultural, language and psychological barriers.
data collected may not be generalisable as it only illustrates the views of those who are able to provide more articulate answers.
Reliability
hard to replicate as the data collected is a person’s unique interpretation of the world
truly consistent findings are unlikely even if same person is tested at a later date since interpretation changes with experience, over time
evidence divulged is done so within the confines of a relationship between two people, (the participant and the researcher), a different researcher might alter the nature of the information provided and the way in which it is recorded and interpreted
This means it is hard to say whether the results are reliable; also decreases the generalisability.