Research Methods Flashcards
Quantitative Data:
Statistics, numbers, focused on measuring patterns, trends. Preferred by Positivists.
Quantitative strengths:
- Easy to analyse.
- Data is a reliable source.
Quantitative Weakness:
- Difficult to understand context of a phenomenon.
- Data may lack in depth information
Qualitative Data:
Quotations from a sample/in depth data that aims to gain a real understanding/ empathy with the topic. Preferred by interpretivists.
Qualitative Strength:
- More in-depth information
- Great for when gathering data on a sensitive topic
- Its usually cheaper
Qualitative Weakness:
- Cannot gain an overall population worth of data
- Hard to analyse
- Data collection is usually time consuming
Main primary Data methods:
- Observation or Ethnographic Study.
- Interviews
- Questionnaire or survey/social survey.
Observation or Ethnographic Study:
- participant.
- non participant.
- overt.
- covert.
What is Participant Observation?
When researcher joins in with the sample.
Strengths of Participant Observation:
- May develop a deeper understanding through sharing experiences.
- Is likely to see a full range of behaviours.
- May influence the group less.
Weaknesses of Participant Observation:
- Researcher can be influenced to perform immoral activities.
- Researcher may get too involved
- May influence the group when joining in activities
What is Non-Participant Observation?
When the researcher stays separate, observes from afar.
Strengths of Non-Participant Observation:
- Can easily observe groups who are different to the observer.
- Can avoid illegal activities.
Weaknesses of Non-Participant Observation:
- Can commit less time to observation.
- May find that subjects act less naturally.
- Will not share the full range of group experiences.
What is Overt Partcipation?
When the researcher tells the sample that they’re observing them.
Strengths for Overt Participation:
- Removes the need to lie and risk being uncovered.
- Notes can be taken openly
Weaknesses for Overt Participation:
- Risks influencing the behaviour of the subjects.
- Makes it difficult to become a full participant.
- May encounter issues from groups not wishing to be observed.
Examples of Overt Participation:
- Maurice Punch (1979)
- William Whyte’s (1955) street corner gangs.
- Incidentally, Whyte’s research was semi-overt (partly open). He revealed his main purpose to a key member of the group, Doc but not to the others.
Examples of Observational Studies:
-Pryce: Conducting a participant observation in an African-Caribbean community in Bristol-taking advantage if his own Western Indian ethnicity. Found the the process exhausting, and was forced to reply on memory to record data.
What is Covert Participation?
When the researcher goes undercover.
Strengths of Covert Participation:
-Enables respondents to act more naturally.
Weaknesses of Covert Participation:
- unethical because as it misleads subjects.
- Difficult to access some groups.
- Makes it difficult to get out of illegal or immoral activities.
- Can render the observer liable to lose objectivity by becoming one of the group.
Examples of Covert Partcipation:
- Laud Humphreys (1970) Homosexual behaviour in male toilets.
- John Howard Griffin (1962) Black like me
- James Patrick (1973) : Glasgow gangs.
Interviews:
- Can be done 1:1 or in group.
- Can be structured/formal, meaning the interview is very pre-planned (a strict list of questions, same as questionnaire but face-to-face).
- Can be unstructured/informal, meaning the interview flows naturally and the interview improvises new questions throughout the interview.
Case Studies examples of Structured interviews:
- Young and Willmott (1962):Interviewed 933 people in research on the family in East London.
- Ann Oakley (1981): Describes interviews as a positivistic and masculine approach to research. Placing high value on objectivity, detachment and hierarchy.
- Fiona Brookman (1999): Difficulty to keep confidential the identity of murderers who have been interviewed, especially in high profile cases.
Case studies examples of Unstructured interviews:
- Michael Parkinson
- Larry king
Questionnaire or Survey/social survey:
- online or through post.
- closed questions (where the respondent selects an answer from a list of options, tick box answers)
- open ended questions (where sample writes the answer freely).
Advantages of Questionnaires:
- It would be reliability
- Respect ethical issues
- A good source for hypothesis testing
Disadvantages of Questionnaires:
- Practical Problem would be detachment
- Questions could be interpreted wrong
- Low Response Rate
Main Secondary Data:
- Official Statistics
- Non-official Statistics
- Using Historical Documents (Diaries, biographies, laws, paintings, novels, photography).
- Content Analysis (Main method to use when analysing the mass media, especially how the media portrays things: internet, films, TV, music. newspapers, magazines).
Official Statistics:
Using data obtained by Government agencies.
Advantages of Official Statistics:
- A reliable source
- Contains large samples
- Can generate a hypothesis for a research
Disadvantages of Official Statistics:
- Difficult to obtain relevant data
- Interpreted according to governments aims
- May lack validity
Non-official Statistics:
Using Data obtained by organisations other than government e.g. charity groups.
Advantages of non-official statistics:
- Can gain an alternative data than what the government perceives to show.
Disadvantages of non-official statistics:
- Data could be unreliable and invalid
Advantages of historical data:
- Can give a qualitative data which gives more information
Disadvantages of historical data:
-More likely to reflect the ideologies of those who wrote them. Unreliable
Advantages of Content Analysis
- Directly examines communication using text.
- Allows for both qualitative and quantitative analysis.
- Coded form of the text can be statistically analysed.
Disadvantages of Content analysis:
- can be extremely time consuming.
- can be difficult to automate or computerise.
Data that positivists prefer:
-Quantitative Data: \+Structured interviews \+Official statistics \+Structured/ closed questionnaires \+Non-participant observation REQUIRES RESEARCH TO BE: reliable, representative and valid.
Data that interpretivists prefer:
- Qualitative Data: \+Unstructured interviews \+Participant Observation \+Non-official statistics \+Unstructured participant observation REQUIRES RESEARCH TO BE: Valid
Main stages of a social survey:
- Choosing a topic
- Create an aim/hypothesis
- Operationalising concepts
- The pilot study
- Sampling
Types of random sampling:
- Representative Sampling
- Simple Random Sampling
- Stratified Random Sampling
- Systematic Sampling
Representative Sampling:
A sample which reflects the group as a whole, the findings of the survey are more likely to apply to the wider society.
Simple Random sampling:
When the researcher obtains a list of names, such as a register of students. Every name is given a number and the sample is selected by using a list of random numbers. Simple random samples are not necessarily representative.
Stratified Random Sampling:
When the sample is randomly selected from one or more of these groups.
It reflects the population as a whole in terms of different groups or strata, such as age or ethnic groups.
Systematic Sampling:
is calculated by dividing the population size by the desired sample size
Types of Non-Random Sampling:
- Quota Sample
- Snowball Sample
- Volunteer Samples
- Purposive Sampling
- Opportunity Sampling
Quota Sample:
A quota sample is like a stratified random sample but the selection is not random. The researcher just fills their quota- e.g. 20 men and 20 women- with the first available people.
Snowball Sample:
A snowball sample builds up like rolling a snowball. The researcher finds one person to fit the sample, that person finds another person and so on. This is useful when people do not want to be identified or are difficult to find- e.g. criminals. drug addicts and sex workers. Snowball sampling is unlikely to produce a representative sample.
Volunteer Samples:
Volunteer samples are drawn from people responding to adverts. Those who volunteer may have a particular reason for doing so- they may have a strongly held point of view or a grievance to express. This may result in an unrepresentative sample.
Purposive sampling:
To produce a sample that can be logically assumed to be representative of the population.
Opportunity Sampling:
An opportunity sample is obtained by asking members of the population of interest if they would take part in your research.
Examples of Historical Data:
- Peter Laslett: Used parish records in his study of family structures in pre-industrial England.
- Phillipe Aries: Used childbearing manuals and paintings of children in his study of the rise of the modern notion of childhood.