Experimental method
Involves the manipulation of an independent variable (IV) to measure the effect of the
dependent variable (DV). Experiments may be laboratory, field, natural or quasi.
Aims
A general statement of what the researcher intends to investigate, the purpose of the study
E.g To investigate whether drinking energy drinks make people more talkative
Experimental/ Alternative Hypothesis
A clear, precise, testable statement that states the relationship between the variables to be
investigated. Stated at the outset of any study.
E.g Drinking coke causes people to become more talkative
Directional - states the direction of the difference or relationship
E.g People who drink coke become more talkative than people who don't
Use when there is previous research on the outcome of the experiment
Non directional - does not state the direction of the difference or relationship
E.g People who drink coke in terms of talkativeness compared to people who don't drink
coke
Use when there is no previous research on the outcome of the experiment
Null hypothesis
There will be no difference any differences is due to chance alone
Extraneous Variables
Any variable, other than the independent variable (IV), that may affect the dependent
variable (DV) if it is not controlled. Evs are essentially nuisance variables that do not vary
systematically with the IV.
Confounding variables
A kind of EV but the kind of key feature is that a confounding variable varies systematically
with the IV. Therefore, we cant tell if any change in the DV is due to the IV or the
confounding variable.
Demand Characteristics
Any cue from the researcher or from the research situation that may be interpreted by
participants as revealing the purpose of an investigation. This may lead to a participant
changing their behaviour within the research situation.
Please-U effect or Screw-U effect
Investigator effects
Any effect of the investigators behaviour (conscious or unconscious) on the research
outcome (the DV). This may include everything from the design of the study to the selection
of, and interaction with, participants during the research process.
E.g leading questions or smiling at participant which could affect result
Randomisation
,The use of chance methods to control for the effects of bias when designing materials and
deciding the order of experimental conditions.
E.g randomly generating a list so the researcher does not decide position of each word
Standardisation
Using exactly the same formalised procedures and instructions for all participants in a
research study.
E.g standardised instructions read to each participant so that non standardised changes do
not act as extraneous variables
Participant variables
Individual differences between participants that may affect the DV
E.g personality, age, gender, motivation, intelligence, concentration
Situational Variables
Any features of the experimental situation that may affect the DV
E.g Noise, time of day, temperature, instructions, weather
Experimental design
The different ways in which participants can be organised in relation to the experimental
condition.
Independent groups
Participants are allocated to different groups where each group represents one experimental
condition. Two separate groups of participants experience two different conditions of the
experiment. The performance is then compared.
Evaluation: Participant variables over the effects of the IV (acts as a confounding variable),
reducing the validity. This can be dealt with by random allocation. BUT, Order effects are not
a problem - ppts less likely to guess the aim.
Repeated measures
All participants take part in all conditions of the experiment. Two mean scores would be
compared.
Evaluation: Order effects - each ppt has to do at least 2 tasks. Could create boredom or
fatigue that might cause deterioration in performance on the second task, so it matters what
order the tasks are in. Alternatively, the ppts performance may improve through the effects of
practice (especially skill based). Order acts as a confounding variable.Demand
characteristics triggered. BUT, participant variables are controlled (higher validity) and fewer
ppts are needed (less time spent).
Matched pairs
Pairs of participants are first matched on some variables that may affect the dependent
variable. One member of the pair is assigned to Condition A and the other to Condition B.
This is an attempt to control for the confounding variables of participant variables.
E.g memory study ppts may be matched on IQ levels
Evaluation: Although, there is some attempt to reduce participant variables in this design,
participants can never be matched exactly. Matching may be time consuming and expensive
, (especially if pretest is involved). BUT, Order effects and demand characteristics are less of
a problem as they only take part in one condition.
Random Allocation
An attempt to control for participant variables in an independent groups design which
ensures that each participant has the same chance of being in one condition as any other.
Laboratory experiment
An environment that 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.
Evaluation: Strengths - High control over confounding and extraneous variables. Any effect
on DV likely from IV. More certain on cause and effect (high internal validity). Replication is
more possible to see if it is valid.
Limitations - Lack generalizability as it is artificial and not like everyday life (low external
validity). ‘Unnatural behaviour’ caused by demand characteristics. Tasks show low mundane
realism.
Field experiment
An experiment that takes place in a natural setting within which the researcher manipulates
the IV and records the effect of the DV.
Evaluation: Strengths - higher mundane realism as the environment is more natural,
therefore, behaviour is more valid and authentic. Participants are unaware they are being
studied (high external validity).
Limitations - Loss of control of CVs and EVs. Cause an effect between IV and DV is more
difficult to establish with replication harder. Ethical issues such as no consent and invasion of
privacy.
Natural experiment
An experiment where the change in the IV is not brought about by the researcher but would
have happened even if the researcher had not been there. The researcher records the effect
on the DV they have decided on.
Evaluation: Strengths - provide opportunities for research that may not otherwise be
undertaken for practical or ethical reasons . High external validity as study of real world
issues and problems as they happen, such as the effects of a natural disaster on stress
levels.
Limitations - Natural events may only happen very rarely, limiting the generalizability.
Participants may not be randomly allocated to experimental conditions (only in independent
groups design). If it is in a lab, it may lack mundane realism and demand characteristics may
be an issue.
Quasi experiments
A study that is almost an experiment but lacks key ingredients. The IV has not been
determined by anyone (the researcher or any person) - the ‘variables’ simply exist, such as
being old and young. Strictly speaking this is not an experiment.
Evaluation: Strengths - Controlled conditions, therefore replication possible as establishment
of cause and effect.
Involves the manipulation of an independent variable (IV) to measure the effect of the
dependent variable (DV). Experiments may be laboratory, field, natural or quasi.
Aims
A general statement of what the researcher intends to investigate, the purpose of the study
E.g To investigate whether drinking energy drinks make people more talkative
Experimental/ Alternative Hypothesis
A clear, precise, testable statement that states the relationship between the variables to be
investigated. Stated at the outset of any study.
E.g Drinking coke causes people to become more talkative
Directional - states the direction of the difference or relationship
E.g People who drink coke become more talkative than people who don't
Use when there is previous research on the outcome of the experiment
Non directional - does not state the direction of the difference or relationship
E.g People who drink coke in terms of talkativeness compared to people who don't drink
coke
Use when there is no previous research on the outcome of the experiment
Null hypothesis
There will be no difference any differences is due to chance alone
Extraneous Variables
Any variable, other than the independent variable (IV), that may affect the dependent
variable (DV) if it is not controlled. Evs are essentially nuisance variables that do not vary
systematically with the IV.
Confounding variables
A kind of EV but the kind of key feature is that a confounding variable varies systematically
with the IV. Therefore, we cant tell if any change in the DV is due to the IV or the
confounding variable.
Demand Characteristics
Any cue from the researcher or from the research situation that may be interpreted by
participants as revealing the purpose of an investigation. This may lead to a participant
changing their behaviour within the research situation.
Please-U effect or Screw-U effect
Investigator effects
Any effect of the investigators behaviour (conscious or unconscious) on the research
outcome (the DV). This may include everything from the design of the study to the selection
of, and interaction with, participants during the research process.
E.g leading questions or smiling at participant which could affect result
Randomisation
,The use of chance methods to control for the effects of bias when designing materials and
deciding the order of experimental conditions.
E.g randomly generating a list so the researcher does not decide position of each word
Standardisation
Using exactly the same formalised procedures and instructions for all participants in a
research study.
E.g standardised instructions read to each participant so that non standardised changes do
not act as extraneous variables
Participant variables
Individual differences between participants that may affect the DV
E.g personality, age, gender, motivation, intelligence, concentration
Situational Variables
Any features of the experimental situation that may affect the DV
E.g Noise, time of day, temperature, instructions, weather
Experimental design
The different ways in which participants can be organised in relation to the experimental
condition.
Independent groups
Participants are allocated to different groups where each group represents one experimental
condition. Two separate groups of participants experience two different conditions of the
experiment. The performance is then compared.
Evaluation: Participant variables over the effects of the IV (acts as a confounding variable),
reducing the validity. This can be dealt with by random allocation. BUT, Order effects are not
a problem - ppts less likely to guess the aim.
Repeated measures
All participants take part in all conditions of the experiment. Two mean scores would be
compared.
Evaluation: Order effects - each ppt has to do at least 2 tasks. Could create boredom or
fatigue that might cause deterioration in performance on the second task, so it matters what
order the tasks are in. Alternatively, the ppts performance may improve through the effects of
practice (especially skill based). Order acts as a confounding variable.Demand
characteristics triggered. BUT, participant variables are controlled (higher validity) and fewer
ppts are needed (less time spent).
Matched pairs
Pairs of participants are first matched on some variables that may affect the dependent
variable. One member of the pair is assigned to Condition A and the other to Condition B.
This is an attempt to control for the confounding variables of participant variables.
E.g memory study ppts may be matched on IQ levels
Evaluation: Although, there is some attempt to reduce participant variables in this design,
participants can never be matched exactly. Matching may be time consuming and expensive
, (especially if pretest is involved). BUT, Order effects and demand characteristics are less of
a problem as they only take part in one condition.
Random Allocation
An attempt to control for participant variables in an independent groups design which
ensures that each participant has the same chance of being in one condition as any other.
Laboratory experiment
An environment that 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.
Evaluation: Strengths - High control over confounding and extraneous variables. Any effect
on DV likely from IV. More certain on cause and effect (high internal validity). Replication is
more possible to see if it is valid.
Limitations - Lack generalizability as it is artificial and not like everyday life (low external
validity). ‘Unnatural behaviour’ caused by demand characteristics. Tasks show low mundane
realism.
Field experiment
An experiment that takes place in a natural setting within which the researcher manipulates
the IV and records the effect of the DV.
Evaluation: Strengths - higher mundane realism as the environment is more natural,
therefore, behaviour is more valid and authentic. Participants are unaware they are being
studied (high external validity).
Limitations - Loss of control of CVs and EVs. Cause an effect between IV and DV is more
difficult to establish with replication harder. Ethical issues such as no consent and invasion of
privacy.
Natural experiment
An experiment where the change in the IV is not brought about by the researcher but would
have happened even if the researcher had not been there. The researcher records the effect
on the DV they have decided on.
Evaluation: Strengths - provide opportunities for research that may not otherwise be
undertaken for practical or ethical reasons . High external validity as study of real world
issues and problems as they happen, such as the effects of a natural disaster on stress
levels.
Limitations - Natural events may only happen very rarely, limiting the generalizability.
Participants may not be randomly allocated to experimental conditions (only in independent
groups design). If it is in a lab, it may lack mundane realism and demand characteristics may
be an issue.
Quasi experiments
A study that is almost an experiment but lacks key ingredients. The IV has not been
determined by anyone (the researcher or any person) - the ‘variables’ simply exist, such as
being old and young. Strictly speaking this is not an experiment.
Evaluation: Strengths - Controlled conditions, therefore replication possible as establishment
of cause and effect.
