Research Methods Flashcards
Self-report Technique
A method where people state or explain their own thoughts/feelings that relate to a given topic
Social-desirability bias
Participants fail to report social undesirable behaviours to appear more likeable
Demand Characteristics
Participants subconsciously change answers after forming idea of what experiment may be about
Response Bias
Responses are biased due to another external factor
Acquiescence bias
Individuals are likely to agree with something regardless of how they feel, and agree with the survey questions rather than own thoughts
Qualitative data
Language based data collection expressed through words, non-numerical
Quantitative data
Numerical data that can be statistically analysed
Open questions
Can add detail to it
More information can be given
Cannot be compared easily
Closed questions
Comparable data
Can’t easily find out extra information, have to follow a script
Interviews
Effort from researcher
Can see the participant and gauge responses
Structured interview
Can be replicated
Standardised, reduced difference between interviewers
Can’t deviate from the topic or explain questions: limits amount of data collected
Unstructured interview
More flexible
Follow up points as they arise
Unexpected information
Interviewer bias
Not easy to analyse the data given
Irrelevant information may be given
Lying for sake of being liked: however, rapport should be built so there are truthful responses given
Semi-structured interview
Follow up questions can be asked
Not easy to compare the data given as different questions asked
Some data can be compared on the questions in common between interviewees
Questionnaires
Cost effective
Large amounts of data collected
Researcher doesn’t need to be present (effort involved is reduced)
Straightforward to analyse
Statistical analysis, comparisons can be made easily
Graphs and charts
May not always be truthful, want to present in positive light (underestimating frequency, for example)
Likert Scale
Respondent indicates agreement with a statement using a scale ranging from Strongly Agree to Strongly Disagree, for example.
Rating Scale
Works in a similar way, but participants identify a value that represents their strength of feeling about a topic (e.g entertaining to not at all entertaining
Fixed-choice option
Includes a list of possible options, and the respondents indicate which of these options apply to them
Interview Schedule
The list of questions that the interviewer wants to cover, and is standardised to avoid interviewer bias
Interview bias
The expectations or opinions of the interviewer interferes with the judgment of the interviewee
Leading question
Question that guides a respondent to a particular answer (e.g ‘Is it obvious that…’)
Emotive Language
Emotive words stir a response in people. Need to be avoided, and neutral words should be used instead of accusing people of things, as this can affect the responses of the participant
Double-Barreled questions
Two questions in one, participants may agree with one half of the question, and not with the other.
Randomisation
Researchers can reduce experimenter effects by using random chance in the design of their experiments.
E.g the order in which words are presented in a memory test are set by chance, rather than the experimenters choice
Standardisation
As far as practically possible, researchers try to ensure all participants have the same experience in the experiment (E.g same place, same time, same test equipment, same interviewer, same questions, same measures of behaviour)
Makes a measure of behaviour RELIABLE (consistent)
Reliability
A measure of whether something stays the same, i.e. is consistent. The results of psychological investigations are said to be reliable if they are similar each time they are carried out using the same design, procedures and measurements
Validity
Whether a measure actually measures what it claims to be measuring, and is true or legitimate
Independent groups/measures
Participants are allocated to either one group or another, and are exposed to different experimental conditions
Repeated measures
The same subjects participate in all conditions of the independent variable
Matched pairs
Overcomes issue of participant variables, matching is done according to a relevant characteristic which might affect behaviour in the study, matches someone in the other condition. Matches may be based on age, gender, skill level, personality, educational attainment etc.
Evaluation of matched pairs
Strengths:
-Can reduce participant variables in an independent groups design
Limitations:
-Matching will never be perfect, even identical twins have differences in attitudes and behaviours
-Process of matching is time consuming
-Pre-testing becomes necessary
-May not be possible within budget
Random allocation
Rather than the researcher deciding who goes in which groups, participants are allocated to each group by random chance
Researcher bias
The beliefs or expectations of the researcher influence the research design or data collection process. Can also be caused by leading questions or emotive language
Counterbalancing
-Improvement to be made to repeated measures design
-Half participants do condition A, followed by B.
-Other half do condition B followed by A, and so distribues order effects (tiredness, practice) across both conditions
Evaluation of random allocation
-Can’t guarantee removal of confounding variables
-Random allocation removes researcher bias from independent measures, but participants in each condition may still be different by chance
Evaluation of Counterbalancing
-Can’t guarantee removal of confounding variables
-Counterbalancing (ABBA), shares out the effect of fatigue or practice across both conditions
-But they are not removed from the experiment
What is discrete data and how it is presented?
If data is made of whole numbers that are counted and not measured, e.g 3 children, 100 workers.
Presented using a bar chart
What is continuous data and how is it presented?
If data is measurable and can take on any value, e.g 3.25kg
Presented through histograms or line graphs
Positively skewed graph
Most scores are at the left of the graph
Long tail on the right
Mode = at the highest point of the peak
Median = next highest
Mean = dragged along to the right
E.g a difficult test in which most students get low marks, and a few get very high marks.
Negatively skewed graph
Most distribution is at the right of the graph
Long tail on the left
Mode = at the highest point of the peak
Median = next
Mean = dragged along to the left
E.g an easy test in which most students get high marks and a few students get very low marks
Bar charts
A type of graph in which the frequency of each variable is represented by the height of the bars
Used when data is divided into categories (discrete data)
Bars do not touch, separated to show a difference in conditions
Histograms
A type of graph which shows frequency but, unlike a bar chart, the area of the bars (not just the height) represents frequency.
The x axis must start at a true zero, and the scale is continuous
Bars are touching, showing continuous data rather than discrete
Scattergrams
A type of graph that represents the strength and direction of the relationship between covariables in a correlational analysis
Do not depict differences but instead depict correlations and associations between co-variables
Line graphs
Represent continuous data
Points are connected with lines to show change in value
What is content analysis?
A type of observational research technique in which people are studied indirectly via the communications they produce.
It is a technique for systematically analysing qualitative information.
It involves drawing up coding categories and counting how often these categories occur.
It converts qualitative data into quantitative data
How is content analysis carried out?
Primary data (unstructured interviews, open questions, unstructured observations)
Secondary data (newspapers, magazines, television adverts, movies, facebook posts, journals texts and graffiti)
Thematic analysis
Similar to a content analysis, the material to be analysed might be any qualitative primary data such as unstructured interview transcripts or secondary data, e.g: diary, TV advertisements, or interview transcripts.
Themes identified are likely to be more descriptive than the coding units in a content analysis.
The themes are not turned into quantitative data.
Once the researcher is satisfied that the themes they have developed cover most aspects of the data adequately, they may review other, similar data to test the validity of these themes.
They may then write up a final report, typically using quotes from the data to illustrate each theme.
Strengths of Content/Thematic analysis
Content/Thematic analysis are both easy techniques to use and help to summarise qualitative information.
They get around ethical issues of conducting research by using secondary data already in the public domain, so consent can be assumed.
Content analysis allows a statistical analysis to be conducted if required since there is quantitative data as a result of the procedure.
Limitations of content/thematic analysis
Content/Thematic analysis merely summarise and describe behaviour; they cannot attribute a cause to that behaviour.
Both Content/Thematic analysis can suffer from subjectivity: when identifying codes/themes the researcher might impose his/her ideas on the content and there is the risk that opinions and motivations are attributed incorrectly.
Content analysis: if the coding units are clearly defined and not open to interpretation, this can be a reliable way of analysing qualitative information as the codes can be applied in the same way over time and with different researchers.
What are the four kinds of experiment?
Lab, field, natural and quasi
Operationalisation
How a variable is clearly defined by the researcher, and defining concepts
Features of a lab experiment
- Takes place in a controlled environment
- IV is controlled/manipulated by researchers
- DV is measured
Features of a field experiment
- Takes place in a natural environment
- IV controlled/manipulated by researchers
- DV is measured
Features of a natural experiment
- IV is a natural or real world even or condition
- NOT manipulated by researchers
- DV is measured
Note: a natural experiment could take place in a lab, but it is the naturally occuring iV that makes it nature, NOT the environment where participants are being tested
Features of a quasi-experiment
- IV is pre existing characteristic (not controlled by researchers)
- DV is measured
Evaluations of lab and field experiments
- Lab and field experiments have control over the IV, greater internal validity
- The lab has the greatest degree of control, a field experiment may be affected by random events outside of the researchers control.
Evaluation of quasi and natural experiments
- Natural and quasi experiments lack control over the IV BUT they are useful, enabling research into variables which for practical or ethical reasons could not be done in a field/lab experiment
-Eg, would not be practical to invent new technologies, but can compare the behaviour of those who have mobiles with those that don’t.
What is sampling?
Process of identifying who will take part in the experiment
Why is sampling important?
Impractical do to psychology by investigating everyone, and so researchers select a few people for their studies, and then generalise the findings from the sample to the target population
Is it okay to generalise from a sample to the whole population?
Yes, BUT the sample and target population should be similar, and so the sample is representative of the target population
Random Sampling
Every member of the target population has an equal chance of being chosen
Systematic Sampling
Uses a predetermined system to select the participants from a target group
Stratified Sampling
Researchers identify subgroups within the target population, and then select a sample with the same sub-group proportions in the target population (ie, representative of age in target population, 10% 18-25 in both population and sample, for example)
Opportunity Sampling
Using people who are conveniently available for the investigation
Volunteer Sampling
Participants self-select to become part of a study because they volunteer when asked, or respond to an advert
What are ethical issues?
Problems faced by psychologists in balancing their needs with the needs of participants. There can be a conflict of interest between the two
What are ethical guidelines?
Set out by the British Psychological Society (in Britain) and are the values and standards that psychologists should follow when doing research
Informed consent
Potential participants should be told in advance what will happen if they get involved in a psychology investigation
Deception
When participants are lied to/not told the full truth about the study.
Deceived participants cannot give fully informed consent
Protection from harm
Participants should be physically and psychologically safe, including: not being embarrassed, ridiculed, pressurised, endangered
Must know they can withdraw at any time
Privacy and confidentiality
People have a right to privacy with their personal information, but researchers often collect personal information (such as feelings/attitudes/reactions), and such information should be confidential
How should privacy be protected for participants by researchers?
Should not to record names/addresses, case studies refer to people by initials, personal data should be stored securely and destroyed once the study is complete, and participants7 are told they can withdraw their data from the study.
Presumptive consent
rather than getting consent from participants, a similar group are asked if the study is acceptable. If they agree, the consent of the original participants is assumed.
Prior general consent
Participants give permission to take part in a number of studies, one of which involved deception, and by consenting, they are saying they are willing to be decieved.
Retrospective consent
Participants are asked for consent having already taken part in the study, and may have not been aware of participation or may have been subject to deception.
Naturalistic Observation
Takes place in a setting/context where target behaviour usually occurs. All environmental aspects vary freely.
Controlled Observation
Watching and recording behaviour within a structured environment where some variables may be managed, e.g. the set up of the room or who enters and leaves the room and the effect it has on the child.
Covert Observation
Participants behaviour is watched and recorded with their knowledge and consent
Overt Observation
When participants know their behaviour is being observed and have given their informed consent beforehand
Participant Observation
Observer becomes part of group they’re studying
Non-participant Observation
When the researcher remains separate from the people they are studying, and records the behaviour in an objective manner
Unstructured Observation
Write down everything you see, qualitative data.
Structured Observation
Record target behaviours only, quantitative data
Behavioural Categories
Precisely defined, observable, measurable
Event Sampling
Record every time a behaviour is observed
Time Sampling
Record what is happening at set intervals
Inter-observer reliability
Measure the level of agreement between observers recording the same behaviour to check consistency
Pilot Study
A practise, trial run, to make sure the experimental procedure works as intended. A pilot study could prompt researchers to improve or modify the procedure so they end up with relevant, useful data.
Single blind procedure
A way to reduce demand characteristics
Participants are not told the:
-study aim
-that there is a control group
-which experimental condition they are in
Double blind procedure
Adds extra level of control to single blind
Researcher who interacts does not know the experimental aim or conditions of the experiment
Control group
Use of a second comparison condition
Essential in any experiment
Provides a benchmark and point of comparison
How the IV affects the DV can only be answered by having a control group
