Research Methods A Flashcards
What various techniques are used in psychology?
Experiments
Observations
Self report
Correlations
The research process
- Review previous research/theories
- Decide on an aim and formulate a hypothesis
- Design a study
- Conduct research
- Analyse and report findings
- Add to/revise theories
What’s an experiment
A way of conducting research where one variable is made to change (independent variable). The effects of the iv on another variable are observed or measured (dependent variable).
Experiments may be laboratory, field, quasi or natural
What’s an aim
A general statement of what the researcher intends to investigate
To see if a loud noise affects participants’ concentration
What’s a hypothesis
A statement of what you believe to be true
Loud noises effect concentration levels more than quiet noises
Directional hypothesis
Predicts the direction of the difference between the two conditions or groups of people. Used when previous research suggests a particular outcome
Non directional hypothesis
Simply predicts a difference between two conditions or groups of people
Used when there is no previous research or existing research is contradictory
Null hypothesis
A statement predicting there will be no difference
Extraneous variables
Any variables other than IV that may have an effect on the DV
Unwanted variables
Types of extraneous variables
Participant variables
Situational variables
Participant variables
To do with differences between participants
E.g. age, gender, intelligence
Situational variables
Features of the experimental situation
E.g. background noise/ light/ difficulty of words
Confounding variables
Any variable besides the IV that may have effected the DV
So we can’t be sure of the true source of changes to the DV
Vary systematically with the IV
E.g. if all people in the music condition: complete the experiment in the evening as opposed to the morning
Demand characteristics
Any cue from the researcher or from the research situation that may be interpreted by participants as revealing the purpose of the investigation
May lead to a participant changing their behaviour within the research situation
Investigator effects
Any effect of the investigator’s behaviour (conscious or unconscious) on the research outcome (DV)
May include everything from the design of the study to the selection of and with participants during the research process
Reducing confounding variables
Randomisation
Standardisation
Randomisation
The use of chance in order to control for the effects of bias when designing materials and deciding the order of conditions
Standardisation
Using exactly the same formalised procedures and instructions for all participants in a research study
Validity
Refers to whether the observed effect is a genuine one
Internal validity
External validity
Internal validity
Degree to which the researcher is measuring what was intended
External validity
Degree to which a research finding can be generalised to other settings, groups of people or over time
Types of experimental design
Repeated measures
Independent groups
Matched pairs
Independent groups design - experimental design
When two separate groups of p’s experience two different conditions of the experiment
If there’re w levels of the IV, all p’s will experience 1 level of the IV
Repeated measures design- experimental design
All participants experience both conditions of the experiment (IV)
Matched pairs design- experimental design
Participants are paired together on a variable or variables relevant to the experiment
Then one p from each pair would be allocated to a different condition of the experiment
Independent groups design issues
The p’s who occupy the different groups aren’t the same
The different found between the groups on the DV may be more to do with individual differences (participant variables) than the effects of the IV
Less economical than repeated measures as each participant contributes a single result only
Independent groups design strengths
Order effects are not a problem
Participants also less likely to guess the aims
What do researchers use in order to deal with the problem of the participants who occupy the different groups bing not the same
Random allocation
Participants are randomly allocated to the different experimental conditions. This attempts to evenly distribute participant characteristics across the conditions of the experiment using random techniques
Repeated measures design issues
Each participant has to do at least two tasks and the order of these tasks may be significant (ie there are order affects)
It’s more likely participants will work out for over the study when the experience or conditions of the experiment. For this reason, demand characteristics tend to be more of a feature of repeated measures design understand independent groups
Repeated Measures design strengths
Participant variables are controlled and fewer participants are needed
What do researcher use to deal with the issue of order affects
Counterbalancing
An attempt to control order effects in the repeated measures design. Half the participants take part in conditions A then B, and the other half take part in conditions B then A
Matched pairs designs issues
Participants can never be matched exactly
Matching may be time-consuming and expensive, particularly if a pre-test is required, so this is less economical than other designs
Matched pair designs strengths
P’s only take part in a single condition so order effects and demand characteristics are less of a problem
Experimental design meaning
The different ways in which the testing of p’s can be organised in relation to the experimental conditions
Types of experiments
Lab
Field
Natural
Quasi
Lab experiment
Takes place in a controlled environment within which the researcher manipulates the IV and records the effect on the DV, whilst maintaining strict control of extraneous variables
Field Experiment
Experiment that takes place in a natural setting within which the researcher manipulates the IV and records the effect on the DV
Natural experiment
Where the change in the IV is not brought about by the researcher but would have happened even if the researcher hadn’t been there
Researcher records effect on DV
Quasi Experiment
A study that’s almost an experiment but lacks key ingredients
IV hasn’t been determined by anyone
Variable simply exist such as being old or young
Lab experiments strengths
High control over extraneous variables. This means that the researcher can ensure that any effect on the dependent variable is likely to be the result of manipulation of the IV.
Thus, we can be more certain about demonstrating cause and effect (high internal validity)
Replication is more possible because of the high level of control. This ensures that new extraneous variables are not introduced when repeating an experiment. Replication is vital to check the results of any study to see whether the findings are valid
Lab experiments limitations
May lack generalisability
Lab environment may be rather artificial and not like everyday life
In an unfamiliar context, p’s may behave in unusual ways so their behaviour cannot always be generalised beyond the research setting (low external validity)
Demand characteristics - acting unnaturally
Task p’s are asked to carry out may not represent real life experience, like recalling unconnected lists of words as part of a memory experiment (low mundane realism)
Field experiments strength
High mundane realism because the environment is natural
Thus will produce behaviour that is more valid and authentic
Especially the case as p’s May be unaware they are being studied (high external validity)
Field experiments limitations
Increased realism = loss of control of extraneous variables
Cause and effect between IV and DV may be more difficult to establish and precise replication is often not possible
Important ethical issues
P’s may be unaware they’re being studied and cannot consent to being studied and such research might constitute an invasion of privacy
Natural experiments strengths
Provides opportunities for research that may not otherwise be undertaken for practical or ethical reasons, such as the studies of institutionalised Romanian orphans
Often have high external validity because they involve the study of real life issues and problems as they happen, such as the effects of a natural disaster on stress levels
Natural experiments limitations
Naturally occurring events may only happen very rarely, reducing the opportunities for research. This also may limit the scope for generalising findings to other similar situations
Participants may not be randomly allocated to experimental conditions. This means the researcher might be less sure whether the IV affected the DV. For Example, in the study of Romanian orphans the IV was when the children were adopted early or late. However there was lots of other differences between these groups, such as those who were adopted late may also have been the less attractive children who no one wanted to adopt
Quasi experiments strengths
Carried out under controlled conditions and therefore share the strengths of lab experiments
High control over extraneous variables
High internal of validity
Replication more possible
Quasi experiments limitations
Cannot randomly allocate participants to conditions and therefore they may be confounding variable
Population definition
Group of people who are the focus of the researcher’s interest
Sample definition
Group of people who take part in a research investigation. Sample is draw for target pop and is believed to be representative of that population
Generalisation definition
Extent to which findings and conclusions from a particular investigation can be broadly applied to the pop
Types of sampling
Random Systematic Stratified Opportunity Volunteer
Random sampling
All members of target pop have an equal chance of being selected
Must obtain a list of all members of the target pop
Use lottery method (computer based randomiser or picking names from a hat)
Systematic sampling
Every nth member of the target pop is selected
A sampling frame is produced, which is a list of people in the target pop organised into, for instance, alphabetical order
A sampling system is nominated e.g. every 3rd person
Stratified sampling
Composition of the sample reflects the proportions of people in certain sub groups (strata) within the target pop
Identify the different strata that make up the pop. Find %
Opportunity sampling
Select anyone who happens to be willing and available
Volunteer sampling
P’s volunteer themselves; self selection
Random sampling pros and cons
+free from researcher bias (don’t have influence over who’s selected)
x difficult and time consuming
x random may still pick an unrepresentative sample
x p’s may refuse to take part
Systematic sampling pros and cons
+ avoids researcher bias
+ fairly representative
x p’s may refuse to take part
Stratified sampling pros and cons
+ avoids researcher bias
+ produces representative sample
+ possible to generalise
x complete representation of target pop is impossible
Opportunity sampling pros and cons
+ convenient- saves time and effort
x unrepresentative sample
x researcher bias
Volunteer sampling pros and cons
+ easy, less time consuming
x volunteer bias- asking for volunteers may attract a certain ‘profile’ of person (e.g. helpful, keen or curios)
What’s a pilot study?
A small scale version of an investigation that takes place before the real investigation is conducted
What’s the aim of a pilot study?
To check that procedures, materials, measuring scales, etc, work and to allow the researcher to make changes or modifications if necessary
What’s primary data?
Information that has been obtained firsthand by the researcher for the purpose of a research project. Such data is often gathered directly from participants as part of an experiment, self-report or observation
What’s secondary data
Information that has already been collected by someone else so pre-dates the current research project
Such data might include the work of other psychologists or government statistics
Primary data pros
Fits the job. Authentic data obtained from the p’s themselves for the purpose of a particular investigation
Primary data cons
Requires time and effort
Secondary data pros
Inexpensive and easily accessed requiring minimal effort
Secondary data cons
May be substantial variation in the quality and accuracy of secondary data
Could be out dated or incomplete
Positively skewed data graph
Right foot
Negatively skewed data graph
Left foot
How to calculate a sign test
Get calculated value S
Get s by adding up the total number of pluses and total number of minuses and then take the number which is lowest
Peer review
The assessment of scientific work by others who are specialists in the same field to ensure that any research intended for publication is of high quality
Operationalisation definition
Clearly defining variables in terms of how they can be measured
A good hypothesis should be…
Stated in the future tense and operationalised
If extraneous variables aren’t controlled, they may become…
Confounding variables
Experimental design definition
The different ways in which the testing of participants can be organised in relation to the experimental conditions
Example of a quasi experiment
Baron-Cohen er al
Got children with Down’s syndrome, children with autism and ‘normal’ children to arrange comic strip stories in to the correct sequence
It was found that the children with autism performed significantly worse when it came to ordering the comic strip
Example of a field experiment
Piliavin et al
Conducted an experiment on a busy New York subway in which a researcher pretended to collapse
It was found that more people helped when the victim was carrying a walking stick than when they smelt of alcohol
Examples of natural experiments
Williams
Monitored the change of behaviour of 6-11 year old children in a Canadian town before and after television was introduced for the first time
Significant increases in levels of aggression was observed after the children had access to tv
Examples of lab experiments
Gilchrist and Nesburg
Deprived patients of food and water for 4 hours and showed them pictures of food
These participants rated the pictures of food as being brighter than the control group who had not been food deprived
Aims of peer review
To allocate research funding
To validate the quality and relevance of research
To suggest amendments or improvements
Why is peer review important
It’s difficult for researchers to spot mistakes in their own work. Other experts are more objective and likely to spot weaknesses and address them
Prevents distribution of irrelevant findings, unjustified claims, and unacceptable interpretations and deliberate fraud
Researchers will look for: validity, quality, originality, significance and credibility
Peer review pros
Anonymity
It is usual that the peer doing the review remains anonymous throughout the process as this is likely to produce more honest appraisal
Peer review cons
Publication bias. It is natural tendency for editors to want to publish headline grabbing findings to increase credibility and circulation. This could mean that research which doesn’t meet the criteria is ignored or disregarded
Anonymity. Some reviewers may use their anonymity to criticise rival researchers, who they perceive as having crossed them in the past
Burying groundbreaking research
