Experiment Flashcards
Research methods
Lab experiment
Observation
Case study
Correlation
Self report
What makes research considered an experiment
Measuring if one factor (IV) effects the DV (what we are measuring) via cause and effect
Independent variable meaning
One factor that is manipulated by the experimenter to see its impact on what the experimenter wants to investigate
Dependent variable
The factor that the independent variable is affected by that the experimenter wants to measure
Control variables
Factors that are kept constant/accounted for to ensure the IV is what affects the DV
And these other factors aren’t the cause
Extraneous variables
Factors that could affect the dependent variable which aren’t the IV
Experimental condition
What some participants experience which the experimenter has manipulated the IV
Control condition
Not been manipulated so provides us with a baseline result which the experimental condition can be compared against
The 3 types of experiment
Lab experiment
Field experiment
Quasi experiment
Lab experiment
IV is manipulated by researchers in a contrived setting (lab eg) away from participants normal in controlled conditions
Field experiment
Independent variable is still manipulated but occurs in participants normal setting
So some factors not necessarily controlled but attempts are made to keep as much constant
Quasi (or natural) experiments
IV of what we want to change is naturally occurring and cannot be manipulated eg weather, race or gender of participants
So occurs over a long period of time where is waited
Lab experiment advantages
Highly controlled to remove extraneous examples, therefore increases construct validity to ensure what we want to measure is measured
Furthermore increased reliability as participants have gone through a standardised procedure
Replicable
Lab experiment disadvantages
Decreased ecological validity as experiment not in natural environment
Being aware you are in an experiment may make behaviour artificial
Field experiments advantages
Behaviour is natural because not under pretence of a study happening (increased ecological validity)
Less chance of displaying demand characteristics to aid the researcher and can’t guess the aim
Field experiments disadvantages
Can be less validdue to extraneous variables not controlled for
Participants can’t give informed consent
Not standardised for all Ps so decerased reliability
Quasi experiments advantages
Naturally occurring so not possible for researcher to be unethical as they cannot change anything
Allows the study of variables psychologists can’t manipulate
Quasi experiment disadvantages
Can be time consuming to wait for IV condition to change
Can be difficult to replicate
Lacks control variables such as lifestyle/ social factors which affect the IV
3 experimental designs
Repeated measures design
Independent measures design
Matched participants design
What are experimental designs?
Ways of setting up an experiment to decide which participants goes into which condition
To control individual participant variables
Repeated measures design
Involves using the same people in each condition so affect of IV is measured against the same person
independent measures design
Involved using different people per condition
Each participant is tested in only 1 condition
Comparing different peoples results against each other
Matched participants design
Involves using different people in each condition however a pre test is done to control participant characteristics by pairing participants on this then putting each into condition to spread what they are matched on across conditions
Advantages of a repeated measures design
Individual differences are controlled because comparisons made for same person
Therefore DV is affected by IV and not individual differences
Requires fewer people than other designs
Disadvantages of repeated measures design
Affects of going through same condition: order effects of boredom, fatigue and practise
Being tested twice may mean they pick up the IV (what is being measured) and show demand characteristics
Advantages of independent measures design
Participants complete it once so results wont be affected by improvement (order effects)
Participants less likely to dropout = not as much effort and less time consuming
Less likely for participants to work out aim of study and show demand characteristics
Disadvantages of independent measures design
Does not control extraneous participant variables so individual differences between participants affect findings
Large samples needed to increase reliability
Advantages of matched participants design
Controls participants variables between than independent measures
No affect or order effects so less likely to be effected by demand characteristics or boredom
Disadvantages of matched participants design
More effort as could involve a pre test beforehand
Requires calculating and achieving a high inter-rater reliability
Impossible to match perfectly because observers may be subjective
What are 2 types of extraneous examples?
Participant variables
Situational variables
Extraneous participant variables
Characteristics of the individual participant that may influence results based on how they respond/ behave other than the IV
Extraneous situational variables
Any feature of the research situation which might influence participants behaviour and affect the result
Examples of participant extraneous variables
Age, intelligence, skill, experience, gender of participant, past experiences
How to control participant extraneous variables?
Same people in each condition = repeated measures design
Or similar people = matched participants design
If using independent measures design randomly allocate each P to the conditions = evenly distributed
Examples of situational extraneous variables
Order effects
Environmental factors
Demand characteristics
Order effects extraneous variables meaning
if doing same activity twice participants may improve the second time so not affected by IV
Or even get worse due to boredom of repeating it
In independent measures design
How to control extraneous situational variables = order effects
Have different people per condition (matched participant or independent)
If repeated measures design then split where group 1 does condition a first then b and group 2 does vice versa
Environmental extraneous variables
Factors including time of day, temperature and noise may change participant behaviour
How to control environmental situational extraneous variables?
Impose variables such as same time of day, same light levels, same temp, same room etc
Demand characteristics = situational extraneous variables
Cues in an experiment which communicate to participants what is expected of them thus unconsciously affect behaviour of participants
How to avoid demand characteristics?
Don’t tell participants aim of the experiment in a single blind experiment
Single bind experiment
Where participants don’t know the aim of the study but the researchers do
Double blind experiment
When neither researchers or participants know the aim of the study
Why would a double blind experiment take place?
To avoid researcher effects
To avoid researcher bias
What are researcher effects?
How research could be affected by a researchers behaviour
Like being more encouraging in experimental condition to prove their hypothesis
What are research bias?
When the researcher expects the data to look a certain way so influences what data
Hypotheses
An intelligent guess as to what the experiment will show based on previous research
2 forms of hypothesis
An alternative hypothesis
A null hypothesis
What is the alternative hypothesis?
Predicts how likely the IV will affect the DV
By stating there will be a SIGNIFICANT DIFFERENCE caused by the IV
2 types of alternative hypothesis
Two tailed
One tailed
Two tailed hypothesis
Predicts the IV will cause a significant difference on the DV but does not say which way eg whether it increases or decreases the DV
One tailed hypothesis
Predicts the IV will have a significant effect in the DV and also the direction this effect goes in
Due to using previous research to predict this
When should you use a two tailed or one tailed alt hypothesis?
One tailed = if previous research exists on the effect of the IV so can predict the direction
Two tailed = if previous research does not exist
Null hypothesis
Predicts the IV will not have an effect on the DV and predicts ‘any difference is due to chance’
What to remember when writing a null hypothesis?
There won’t be a SIGNIFICANT difference in __(DV)__ when the experiment takes place in condition 1 or condition 2 (IV, state what it is). ANY DIFFERENCE WILL BE DUE TO CHANCE
What to remember when writing an alt one tail hypothesis?
There will be a significant increase/decrease in the DV when the experiment takes place in condition 1 rather than condition 2 (IV, state it)
What to remember when writing alt two tail hypothesis?
There will be a significant DIFFERENCE in the DV when the experiment takes place in condition 1 rather than condition 2
What must be done to the DV and IV when writing a hypothesis?
Operationalise it
Operationalisation
The process of making abstract variables such as personality traits measurable (if as a DV) or testable (if as a IV)
Example of operationalising an IV in terms of sportiness
For example if the sportiness of participants was the IV of the experiment
Sporty people = completes exercise 3 times a week
Non sporty people = less than 3 times
Example of operationalising a DV in terms of sportiness
The experiment will measure the sportiness of the participant
So measure whether they can complete a lap around a pitch within under a certain time frame
