RESEARCH METHODS
Aims & Hypotheses:
AO1
The aim of a study is a general statement covering the theory that will be
investigated
The aim identifies the purpose of the experiment
A hypothesis is a testable statement written as a prediction of what the researcher
expects to find as a result of their experiment
The alternative hypothesis has the operationalised IV and DV
Directional hypothesis is one tailed and predicts the direction of the difference
Non-directional hypothesis is two tailed and does not predict the direction of
difference
Null hypothesis, the idea that the IV will not affect the DV
For correlations instead of writing ‘there will be a difference’ it is ‘there will be a
relationship’
Variables:
AO1
Independent variable is what is changed
Dependant variable is what is measured
Extraneous variables are any factors that could affect the DV, they are usually
controlled for
If extraneous variables are not controlled they become confounding variables
Confounding variables can affect the DV and negatively impact the research findings
Research Issues and Controls:
AO1
Demand Characteristics- please u and screw u effect
o Control by using a single-blind procedure
Investigator effects- when the researchers behaviour interferes and becomes a
source of bias
o Control using a double-blind procedure
Randomisation is the deliberate avoidance of bias by keeping the research as
objective as possible such as randomly assigning participants to each condition
Standardisation is the use of identical procedures across all conditions and
participants so that none are treated any differently
Pilot Studies:
AO1
Pilot studies are small-scale trials that are run to test some or all aspects of the
proposed investigation
They are conducted before the research to identify any issues such as flaws in the
design, ethical issues, feasibility issues, reliability, and validity
Pilot studies can also be used as evidence to obtain funding
Types of Experiments:
, AO1
Lab experiment- high levels of control, standardised procedures
Field experiment- takes place in a natural setting, less control, still involve
implementation of IV and DV
Natural experiment- research in naturally occurring phenomena, cannot manipulate
the IV, real world setting
Quasi experiment- does not manipulate IV, IV already exists in participants
AO3
Lab experiments- can establish a cause-effect relationship, high internal validity,
replicable, lack ecological validity, demand characteristics limit generalisability
Field experiment- high in external validity, less likely to experience demand
characteristics, extraneous variables much more likely, difficult to replicate
Natural experiment- investigate topics that would otherwise be unethical, high in
ecological validity, elevates mundane realism, causal relationships hard to
determine, social desirability bias, confirmation bias, sample bias
Quasi experiment- higher in external validity, could be replicated, participant
variables as participants can’t be randomly allocated, lack internal validity
Experimental Design
AO1
Independent Groups- participants only experience one condition of the IV and
generates unrelated data
For independent groups random allocation can be done to avoid researcher bias
Repeated Measures- participants experience all conditions of the IV and generates
related data
Repeated measures give rise to order effects such as fatigue, boredom, or practice.
To avoid this researchers must use counterbalancing
Matched Pairs- participants are matched based on a specific characteristic or
variable, they can be matched on more than one variable, matched participants are
then randomly allocated
AO3
Independent Groups- demand characteristics unlikely, order effects eliminated,
participant variables may affect validity, more participants needed
Repeated Measures- participant variables not an issue, fewer participants needed,
demand characteristics may become a confounding variable, order effects can lower
the validity if not controlled
Matched Pairs- factors out individual differences as a confounding variable, demand
characteristics reduced, difficult and time consuming, if someone drops out this
creates issues
Sampling Techniques:
AO1
At the beginning the researcher must identify the target population e.g. people who
live in large cities in the UK
The researcher is taking a sample from the population to take part and then
generalising these findings to the target population
Aims & Hypotheses:
AO1
The aim of a study is a general statement covering the theory that will be
investigated
The aim identifies the purpose of the experiment
A hypothesis is a testable statement written as a prediction of what the researcher
expects to find as a result of their experiment
The alternative hypothesis has the operationalised IV and DV
Directional hypothesis is one tailed and predicts the direction of the difference
Non-directional hypothesis is two tailed and does not predict the direction of
difference
Null hypothesis, the idea that the IV will not affect the DV
For correlations instead of writing ‘there will be a difference’ it is ‘there will be a
relationship’
Variables:
AO1
Independent variable is what is changed
Dependant variable is what is measured
Extraneous variables are any factors that could affect the DV, they are usually
controlled for
If extraneous variables are not controlled they become confounding variables
Confounding variables can affect the DV and negatively impact the research findings
Research Issues and Controls:
AO1
Demand Characteristics- please u and screw u effect
o Control by using a single-blind procedure
Investigator effects- when the researchers behaviour interferes and becomes a
source of bias
o Control using a double-blind procedure
Randomisation is the deliberate avoidance of bias by keeping the research as
objective as possible such as randomly assigning participants to each condition
Standardisation is the use of identical procedures across all conditions and
participants so that none are treated any differently
Pilot Studies:
AO1
Pilot studies are small-scale trials that are run to test some or all aspects of the
proposed investigation
They are conducted before the research to identify any issues such as flaws in the
design, ethical issues, feasibility issues, reliability, and validity
Pilot studies can also be used as evidence to obtain funding
Types of Experiments:
, AO1
Lab experiment- high levels of control, standardised procedures
Field experiment- takes place in a natural setting, less control, still involve
implementation of IV and DV
Natural experiment- research in naturally occurring phenomena, cannot manipulate
the IV, real world setting
Quasi experiment- does not manipulate IV, IV already exists in participants
AO3
Lab experiments- can establish a cause-effect relationship, high internal validity,
replicable, lack ecological validity, demand characteristics limit generalisability
Field experiment- high in external validity, less likely to experience demand
characteristics, extraneous variables much more likely, difficult to replicate
Natural experiment- investigate topics that would otherwise be unethical, high in
ecological validity, elevates mundane realism, causal relationships hard to
determine, social desirability bias, confirmation bias, sample bias
Quasi experiment- higher in external validity, could be replicated, participant
variables as participants can’t be randomly allocated, lack internal validity
Experimental Design
AO1
Independent Groups- participants only experience one condition of the IV and
generates unrelated data
For independent groups random allocation can be done to avoid researcher bias
Repeated Measures- participants experience all conditions of the IV and generates
related data
Repeated measures give rise to order effects such as fatigue, boredom, or practice.
To avoid this researchers must use counterbalancing
Matched Pairs- participants are matched based on a specific characteristic or
variable, they can be matched on more than one variable, matched participants are
then randomly allocated
AO3
Independent Groups- demand characteristics unlikely, order effects eliminated,
participant variables may affect validity, more participants needed
Repeated Measures- participant variables not an issue, fewer participants needed,
demand characteristics may become a confounding variable, order effects can lower
the validity if not controlled
Matched Pairs- factors out individual differences as a confounding variable, demand
characteristics reduced, difficult and time consuming, if someone drops out this
creates issues
Sampling Techniques:
AO1
At the beginning the researcher must identify the target population e.g. people who
live in large cities in the UK
The researcher is taking a sample from the population to take part and then
generalising these findings to the target population
