Introduction to Psychological investigations Flashcards
What are variables?
Variables are anything that can be measured or controlled.
- All variables must be operationalized. This means that there must be a precise description for all variables that are being measured or controlled
Examples of variables
- height
- age
- gender
- shoe size
Independent variables
the experimenter manipulates or changes, and causes the change in dependent variables
Dependent variables
the variables being tested and measured in a experiment.
Operationalising variables
how you define and measure a specific variable
Standardisation
the process in which procedures used in research are kept the same.
demand characteristics
(extraneous variable)
The Participants deliberately change their behaviour. The Participants tried to act favourably for the researcher.
All the 4 types of experiments have characteristics in common.
- variables - IV + DV
- Controlled variables
- cause and effect established
- small sample size
Laboratory Experiments
- conducted under controlled conditions,
Strengths - Control – lab experiments have a high degree of control over the environment & other extraneous variables which means that the researcher can accurately assess the effects of the I.V, so it has higher internal validity.
- Replicable – due to the researcher’s high levels of control, research procedures can be repeated so that the reliability of results can be checked.
Limitations
Lacks ecological validity – due to the involvement of the researcher in manipulating and controlling variables, findings cannot be easily generalised to other (real life) settings, resulting in poor external validity. - Ps show or demonstrate demand characteristics
Field Experiments
These are carried out in a natural setting, in which the researcher manipulates something (I.V.) to see the effect of this on something else (D.V.).
Validity – field experiments have some degree of control but also are conducted in a natural environment, so can be seen to have reasonable internal and external validity.
Limitations
Less control than lab experiments and therefore extraneous variables are more likely to distort findings and so internal validity is likely to be lower.
Natural Experiment
The researcher does not control the IV they occur naturally. Strengths
High ecological validity – due to the lack of involvement of the researcher; variables are naturally occurring so findings can be easily generalised to other (real life) settings, resulting in high external validity.
Limitations
Lack of control – natural experiments have no control over the environment & other extraneous variables which means that the researcher cannot always accurately assess the effects of the I.V, so it has low internal validity.
Not replicable – due to the researcher’s lack of control, research procedures cannot be repeated so that the reliability of results cannot be checked.
Quasi Experiments
- investigator lacks complete control of the IV or the allocation of participants to groups
Sampling
- must be representative
- population validity is increased when the sample is representative of the target population.
- The more representative the sample the more the results can be generalised to other members of the population.
- if it’s unrepresentative then there is a limitation in the investigation
- cannot be generalised to the target population or it will have a bias
- ## if all members are included that means we will have different findings
Random sampling
This method gives every member of the target group an equal chance of being selected for the sample (e.g. by assigning a number to each member, and then selecting from the pool at using a random number generator)
Strengths
It is widely accepted that since each member has the same probability of being selected, there is a reasonable chance of achieving a representative sample.
Weaknesses
Small minority groups within your target group may distort results, even with a random sampling technique.
It can be impractical (or not possible) to use a completely random technique, e.g. the target group may be too large to assign numbers to.
Systematic sampling
uses a sampling frame at regular intervals..g. every fourth person in a list could be used in the sample.
Strengths
Assuming the list order has been randomised, this method offers an unbiased chance of gaining a representative sample.
Weaknesses
If the list has been assembled in any other way, bias may be present. eg, if every fourth person in the list was male, you would have only males in your sample.
- time consuming in the end participants may refuse to take part
Stratified Sampling
he target group into sections, each showing a key characteristic which should be present in the final sample. Then each of those sections is sampled individually.
Strengths
It avoids the problem of misrepresentation sometimes caused by purely random sampling.
Weaknesses
It takes more time and resources to plan.
Care must be taken to ensure each key characteristic present in the population is selected across strata, otherwise this will design a biased sample.
Opportunity Sampling
Participants who are both accessible and willing to take part are targeted
Strengths
This method is easy and inexpensive to carry out.
Weaknesses
The consequent sample may not be representative as it could be subject to bias
Volunteer Sampling
Here the sample consists of people who have volunteered to be in the study. Strengths
This often achieves a large sample size by reaching a wide audience, for example with online advertisements.
Weaknesses
Those who respond to the call for volunteers may all display similar characteristics thus increasing the chances of yielding an unrepresentative sample.
- difficult to generalise findings unrepresentative
Advantages and Disadvantages of Questionnaires
strengths
Questionnaires are a relatively cheap and quick way to gather a large amount of data.
Since questionnaires can be completed privately (and often anonymously), responses may be more likely to be honest. However, not having an experimenter to supervise its completion could present a problem.
- open questions tend to produce qualitative data that is rich in depth and detail but may be difficult to analyse
Weaknesses
Social desirability issues may arise, where participants give incorrect responses to try to put themselves in a socially acceptable light.
Distributing questionnaires en masse (e.g. via post or the internet) means that any data collected relies on responses to be returned; response rates are often poor, plus it may be that only a certain type of person returns questionnaires, so generalising the sample of results to a large population can be unconvincing.
Questionnaires may be flawed if some questions are leading (i.e. they suggest a desired response in the way they are worded).
If any questions are misunderstood, participants completing questionnaires privately cannot get clarification on the meaning/responding accurately from an experimenter, so may complete them incorrectly.
Advantages and Disadvantages of interviews
Strengths:
- Unstructured interviews provide potential to gather rich and detailed information from each participant – more so than questionnaires.
- The conversational nature of unstructured interviews is best suited to discussing complex or sensitive issues, as participants are more likely to relax and give better responses as the dialogue flows.
- Interviews can be used as part of a pilot study to gather information prior to conducting proposed research.
Weaknesses:
- There is a lot of time and expense involved when training interviewers, to conduct unstructured interviewers in particular.
- Social desirability bias can be a problem with self-report techniques, i.e. participants give responses that are thought to be the most socially acceptable, rather than necessarily truthful.
- Interview data can be a time-consuming task to analyse and interpret when it is so detailed (and in a qualitative [written] format).
- Interviews require participants to have basic competencies for interviews to be successful (e.g. adequate communication skills, memory, honesty) which could potentially limit the sample’s size and representativeness of the population if not met.
What are the 2 types of interviews
Structured – where the interviewer has a set list of questions to lead the conversation, a framework which will be rigidly stuck to
Unstructured – where the interviewer may have a list of topics or questions but has extra flexibility to lead the conversation further, should participant responses lead to deeper/more detailed discussion
Repeated Measures Design
Where the same participants are allocated to all groups (i.e. take part in all conditions) of an experiment.
Strengths and Weakness of repeated measures design
strengths
- The results will not be subject to participant variables (i.e. individual differences between participants), putting more confidence in dependent variable changes being solely due to manipulated changes in the independent variable.
- As the same participants are used [at least] twice, extra participants do not need to be recruited.
Weaknesses
- There is risk of observing order effects (e.g. practice / fatigue effects, or demand characteristics), but this risk be reduced by counterbalancing (i.e. controlling the order of variables so that each order combination occurs the same number of times, e.g. one half of participants partake in condition A followed by B, whereas the other half partake in B followed by A).
- If a participant drops out, data will be lost from all conditions of the experiment rather than one.
Independent Groups Design
Where different participants take part in each experimental condition (they will be allocated randomly).
