Experimental Method Flashcards
(25 cards)
Aim
Establish a cause and effect relationship between 2 variables
In order to establish a cause and effect relationship, what must be done?
Experiments must be performed under highly controlled conditions
Aiming for a cause and effect relationship
Seeing whether a changed in the independent variable (IV) causes a changed in the dependent variable (DV)
Independent variable
The variable that the researcher deliberately manipulates
Dependent variable
The variable that is being measured after the manipulation of the independent variable
In order to see the effect of the IV on the DV, what do the variables have to be?
The variables need to be operationalised - written in a way it is clear what is being measured
In order to formalise the aim, what do the researchers need to develop?
Researchers must develop a hypothesis
Hypothesis
Predicts the relationship between the IV and the DV (how IV affects DV)
What are the different types of experiments?
Laboratory, field and natural
Laboratory experiment
- takes place in a laboratory (artificial environment)
- IV is manipulated and the rest are controlled
- the environment is controlled and the procedure is standardised
Strengths of laboratory experiments
- can establish a cause-effect relationship
- easy to replicate
- present variable control + accuracy of measurements
Weaknesses of laboratory experiments
- artificiality leads to lack of ecological validity
- biased - demand of characteristics + experimenter effect
Field experiment
- natural environment
- variables are manipulated
Strengths of field experiments
- more ecological validity compared to lab experiments as the behaviour occurs in a natural environment
- fewer demand characteristics
Weaknesses of field experiments
- nearly impossible to replicate
- cannot control all the variables -> confounding variables
Natural expierment
- natural environment
- IV is naturally occurring
- no variables are manipulated
Strengths of natural experiments
- ecological validity - focuses on a natural environment
- very little bias from demand characteristics
Weaknesses of field experiments
- impossible to establish a cause-effect relationship
- impossible to replicate
Points to consider with experiments
Participant variability, researcher bias, artificiality, confounding variables, demand characteristics
Participant variability
The extent in which participants may share a common set of traits that can bias the outcome of the study; important to consider when choosing a sample to avoid over representation of traits
How can participant variability be controlled?
Random sampling
Researcher bias (observer bias)
When the experimenter finds what he/she is looking for; expectations affect the findings of the study
Artificiality
A term used when the situation created is so unlikely to occur that one has to consider the ecological validity in the findings
Confounding results
Undesirable variables that influence the relationship between IV and DV
