Research methods
Experimental methods:
• Aim - A statement in outlining what an experiment and a study is interested in finding out. It
is developed from theories and developed from reading about other similar research.
Types of Hypotheses:
• Hypothesis - An accurate statement which states the relationship between the variables
being investigated.
- Directional Hypothesis (One-Tailed) - is when the direction of the difference is predicted
based on previous studies.
- Non-Directional Hypothesis (Two-Tailed) - is used when the direction of the difference can
not be predicted and usually used when there are not previous studies or when the previous
studies are contradictory.
- Null Hypothesis - is predicting no difference will be found in the result between the
conditions.
- Alternative Hypothesis - these will predict there will be a significant difference in the result
between the two conditions and it must be operationalised.
Types of Variables:
• Independent Variables - it is when the researcher manipulates and changes the conditions
the participants are placed into, and it has a direct effect on the dependent variable.
• Dependent Variable - it is the variable that is being measured or the result of a study.
• Operationalisation of Variables - it is to be accurate and clear about what is being
manipulated or measured and we must use operationalisation to ensure that variables are in
a form that can be easily tested. For example, we can't measure 'happiness but we can
measure how many times a person smiles within a two hour period.
• Extraneous Variables - it refers to any other variable which is not the IV that may affect the
DV which is the result of a study. For example, Age of participants or lighting in a lab.
• Confound Variables - it is described as a type of extraneous variable that is related to the
IV in a study. For example, if testing the effects of anxiety on memory recall, the relative
levels of sensitivity to anxiety-inducing stimuli would be a confounding variable,
Types of Extraneous Variables:
• Demand Characteristics - this happens when the participants figure out the aim of the
study and they may behave in a certain way to be more desirable and this can be dealt with
by Single Blind Design which is when participants are not aware of the aim and also not
aware of the conditions they are receiving. For example, in a drug study, participants do not
know whether they have taken a drug or placebo.
• Investigator Effects - refers to any unintentional effect of the researcher's behaviour that
might affect the particionat's behaviour for example, researcher's body language and facial
, expressions. and it will affect the result of the study. It can be dealt with by providing a
standardised script for the investigator to use so that they ask questions in the same way.
• Participants Variable - refers to individual differences between the participants that will
impact the outcome of the study (DV). for example, age, intelligence, personality and
experience of the participants. It can be dealt with by using random allocation or matched
pairs designs to ensure that the groups are smaller
Experimental designs:
Experimental design refers to how participants are allocated to each condition of the
independent variable, such as control or experimental group.
Types of experimental designs
• Independent Measures - Two groups in a study and each group taking part in different
conditions. Group 1 - Condition A and Group 2 - Condition B
- Solution: Random Allocation, it ensures that each participant has the same chance of being
in one condition of the IV as another.
- Strength: Participants are less likely to figure out the aim of the study which Limitation:
Participants Variable, the two groups may not be equal in terms of IQ, Age or personality this
might create confound variables and twice as many participants would be needed than the
other designs which makes it
• Repeated Measures - it refers to when each participant takes part in both
- Solution: counterbalancing, this is when half the participants do conditions in one order and
the other half do it in an opposite order.
- Strength: less cost effective, this is because it gives two bits of data for each participant
which means fewer participants needed. Also, it rules out participant variables because the
same people are used so gender, age and other extraneous variables can't be changed or
affect the outcome.
- Limitation: Order Effects, this means the participants may respond differently to the second
task because they completed both conditions.
• Matched Pairs - it is when participants are matched based on their similarities and they are
put in different groups.
- Solution: no solution required.
- Strength: No order effects because only one condition has been experienced by each
participant and demand characteristics are less of a problem.
- Limitation: participants can never be matched perfectly, therefore there may still be
participant variable influence on the results and it is more time consuming and expensive as
pre tests might be required to match participants.
Experiment description strength limitation
Experimental methods:
• Aim - A statement in outlining what an experiment and a study is interested in finding out. It
is developed from theories and developed from reading about other similar research.
Types of Hypotheses:
• Hypothesis - An accurate statement which states the relationship between the variables
being investigated.
- Directional Hypothesis (One-Tailed) - is when the direction of the difference is predicted
based on previous studies.
- Non-Directional Hypothesis (Two-Tailed) - is used when the direction of the difference can
not be predicted and usually used when there are not previous studies or when the previous
studies are contradictory.
- Null Hypothesis - is predicting no difference will be found in the result between the
conditions.
- Alternative Hypothesis - these will predict there will be a significant difference in the result
between the two conditions and it must be operationalised.
Types of Variables:
• Independent Variables - it is when the researcher manipulates and changes the conditions
the participants are placed into, and it has a direct effect on the dependent variable.
• Dependent Variable - it is the variable that is being measured or the result of a study.
• Operationalisation of Variables - it is to be accurate and clear about what is being
manipulated or measured and we must use operationalisation to ensure that variables are in
a form that can be easily tested. For example, we can't measure 'happiness but we can
measure how many times a person smiles within a two hour period.
• Extraneous Variables - it refers to any other variable which is not the IV that may affect the
DV which is the result of a study. For example, Age of participants or lighting in a lab.
• Confound Variables - it is described as a type of extraneous variable that is related to the
IV in a study. For example, if testing the effects of anxiety on memory recall, the relative
levels of sensitivity to anxiety-inducing stimuli would be a confounding variable,
Types of Extraneous Variables:
• Demand Characteristics - this happens when the participants figure out the aim of the
study and they may behave in a certain way to be more desirable and this can be dealt with
by Single Blind Design which is when participants are not aware of the aim and also not
aware of the conditions they are receiving. For example, in a drug study, participants do not
know whether they have taken a drug or placebo.
• Investigator Effects - refers to any unintentional effect of the researcher's behaviour that
might affect the particionat's behaviour for example, researcher's body language and facial
, expressions. and it will affect the result of the study. It can be dealt with by providing a
standardised script for the investigator to use so that they ask questions in the same way.
• Participants Variable - refers to individual differences between the participants that will
impact the outcome of the study (DV). for example, age, intelligence, personality and
experience of the participants. It can be dealt with by using random allocation or matched
pairs designs to ensure that the groups are smaller
Experimental designs:
Experimental design refers to how participants are allocated to each condition of the
independent variable, such as control or experimental group.
Types of experimental designs
• Independent Measures - Two groups in a study and each group taking part in different
conditions. Group 1 - Condition A and Group 2 - Condition B
- Solution: Random Allocation, it ensures that each participant has the same chance of being
in one condition of the IV as another.
- Strength: Participants are less likely to figure out the aim of the study which Limitation:
Participants Variable, the two groups may not be equal in terms of IQ, Age or personality this
might create confound variables and twice as many participants would be needed than the
other designs which makes it
• Repeated Measures - it refers to when each participant takes part in both
- Solution: counterbalancing, this is when half the participants do conditions in one order and
the other half do it in an opposite order.
- Strength: less cost effective, this is because it gives two bits of data for each participant
which means fewer participants needed. Also, it rules out participant variables because the
same people are used so gender, age and other extraneous variables can't be changed or
affect the outcome.
- Limitation: Order Effects, this means the participants may respond differently to the second
task because they completed both conditions.
• Matched Pairs - it is when participants are matched based on their similarities and they are
put in different groups.
- Solution: no solution required.
- Strength: No order effects because only one condition has been experienced by each
participant and demand characteristics are less of a problem.
- Limitation: participants can never be matched perfectly, therefore there may still be
participant variable influence on the results and it is more time consuming and expensive as
pre tests might be required to match participants.
Experiment description strength limitation
