RESEARCH METHODS & SAMPLING TECHNIQUES Flashcards
Strengths of quantitive data
- It’s objective - making it easy to analyse and compare data.
-As it’s not open to interpretation, it’s also a lot less time-consuming meaning more data can be collected which makes the research more reliable and easier to generalise. - Reliable and highly scientific because the reseach do not need to be personally interpreted, it is clear and objective
Weaknesses to quantitive data
- Numerical data only tells you how often behaviour occurs not the underlying motivation or thoughts - this undermines the research validity
- It cannot generate qualitative data whereas qualitative data can be broken down to generate quantitive data
Strengths to qualitative data
- It produces more detail and allows researchers to make more in-depth conclusions (high ecological validity)
- It can be broken down into quantitive data
Weaknesses to qualitative data
- It’s difficult to analyse statistically and therefore hard to generalise from
-It’s more likely subjective research which is open to interpretation, opinions and research a bias (low internal validity)
Examples of quantitive data
Numerical data, closed questions or likert/ranking scale
Examples of qualitative data
Open-ended surveys, self report data, interviews, case studies
What are open questions?
Questions that can be answered subjectively, participants can explain and express opinions. It is not a numerical or straight up response.
What are closed questions?
Questions that have a fixed/limited amount of responses. They are very clear and objective
E.g - yes or no or multiple choice
What is the likert/ranking scales?
Where participants rate their opinion/attitude through multiple choice or a numerical value
What is self report data?
Information elicited from questions that rely on participants reporting their own behaviour/feelings
E.g - interviews
2 advantages of the likert/ranking scales
- Easy to analyse and compare data
- ## Less time consuming so more data can be produced, it can be easily replicated and reliable therefore more generalisable
2 disadvantages of the likert/ranking scales
- They do not generate in-depth, quality responses and participants cannot expand on their views so it may not be an accurate reflection of their thoughts/behaviour
- Pps may have different opinions to the options available - therefore it is restricting the pps from answering honestly and reducing the validity of the research
Strength and weaknesses of closed questions
S
- Easy to replicate for reliability
- Easy to interpret and statistically analyse - objective
- Well controlled as the questions require a clear defined response
W
- Demand characteristics I’m more likely to occur as there are ‘socially desirable answers’ - reducing validity
- Limited options may produce a lack of engagement
Strength and weaknesses of open questions
S
- Detailed and more valid in-depth responses as people can express their opinions
- Good way of accessing pps motivations and feelings
W
- Subjective interpretation means low reliability
- Hard to analyse statistically
- More time consuming meaning less participant data meaning less generalisable
Strengths and weaknesses of self-report data
S
- More detail into participants thoughts and feelings
- Psychologist can investigate future behaviour from pps from their thought processes
- Pps can use their own experiences increasing the ecological validity
W
- Relies on honest, insightful, articulate pps
- Pps may give ‘socially desirable answers’ to reflect social norms
What is a questionnaire?
A set of predetermined questions aimed to elicit the attitudes and opinions of participants about an issue
Strengths and weaknesses of questionnaires
S
- Time and cost-effective - they can be quickly administered online
This means more people can take part making the results more reliable and generalisable
- Private and anonymous = more honest opinions which improves validity
- Reduced researcher involvement reduces the chance of researcher bias
W
- Response rates can be poor without the presence of a researcher which makes the results hard to generalise
- It may be that only certain types of people take part in questionnaire - not representative of a wider population
- Be difficult to phrase questions in ways that are objective for pps to answer
What is an interview?
When the researcher and participants engage in a face-to-face conversation gaining verbal information
Strengths and weaknesses of interviews
S
- A well conducted interview can address sensitive issues that other methods are not able to address
- A good source of qualitative data
W
- Research a bias and demand characteristics are more likely
- It may only be confident, honest and articulate individuals who volunteer which is not representative of a wider population
- The research is highly dependent on the skills of the interviewer especially with unstructured interviews
Unstructured vs Semi-structured vs Structured interview
Unstructured - questions are open ended and each question depends on answers previously given. Qualitative data. Interview needs to be highly skilled so can be analytical and establish meaning from the participants answers
Semi-structured - a schedule of questions but some flexibility to expand on responses
Structured - systematic, standardised, pre-determined questions that are the same for everyone
Strengths of unstructured and structured interviews
Unstructured - They’re flexible, more detail, can expand on answers, information about attitudes, beliefs and underlying behaviour giving high validity
Structured - very reliable as they’re easy to repeat/administer. Easy to compare answers. Less chance of researcher bias and validity as answers do not need to be individually interpreted
Disadvantages to unstructured and structured interviews
Unstructured - cannot be replicated, on systematic, time-consuming, subjective interpretation. Greater potential ethical issues as qualitative data requires direct reference to participant quotes in detail details while research needs to be anonymised and confidential.
Structured - less detail elicited as little opportunity to expand on answers. Lower validity as pps may feel unable to express their opinion fully.
Types of sampling
Random - every member of the target population has an equal chance of taking part in the research like names in a hat or a computer generator
Opportunity - participants selected from whoever is available at the time
Stratified - a proportional representation of the target population e.g. 60% male and 40% female
Volunteer - participants select themselves
Strengths for all sampling types
Random - most representative, unbiased as the researcher has no influence. Results can be easily generalised.
Opportunity - ethical, easy and quick meaning you can get a large sample and make results more reliable
Stratified - likely to be very representative of the target population
Volunteer - well motivated so likely to give useful feedback, less likely to drop out, easy
Weaknesses for all sampling types
Random - very hard to do unless you have a small population group. If some participants refuse, the sampling may still end up being unrepresentative.
Opportunity - not very representative as the sample is drawn from who is available at the time (similar traits and behaviour) limiting generalisability
Stratified - time consuming and difficult to establish correct proportions from the target sample populations. If all the key features of the target population are not identified than the sample may not be representative.
Volunteer - As volunteers are highly motivated they may behave differently to others which is not representative and limits generalisability. They may also show demand characteristics.
What is qualitative data thematic analysis?
A technique used to identify patterns of meanings. Patterns, trends and themes within qualitative data. It is used with methods such as content analysis, case studies and self report measures
Thematic analysis carries a risk of subjectivity and research a bias as identification of themes/patterns/trends requires an element of interpretation. It’s possible that the researchers beliefs and expectations impact how qualitative data is analysed.
