EXPERIMENTS Flashcards
Experimental method
Manipulate situations, deliberately set up situations, watch and record what happens.
Experiments have an IV and a DV.
Independent variable
Made to change by experimenter
Dependent variable
Observed/ measured by experimenter
Cause and effect relationship
Relationship between two events/ situations, one of the two is cause of the other.
Control other variables as well as measuring IV and DV allows us to test cause and effect.
comparison condition
To find out if IV affected DV, this condition is where there is a different level of the IV.
3 Experimental designs
Independent measures
Repeated measures
Matched pairs
Independent measures design
Using different ps in each condition.
E.g giving one group of ps one test and a different group the same but in a different condition.
Giving one group a driving test after alcohol, and another group the same test sober.
Strengths of IMD
-NO ORDER EFFECTS- practice; 2nd time may be better
fatigue; 2nd time ps may be worse, bored.
-REDUCE EXPOSURE TO DEMAND CHARACTERISTICS- ps only see condition one time, less likely to change their behaviour.
Weaknesses of IMD
-INDIVIDUAL DIFFERENCES- intelligence levels can differ and distort results between conditions.
-MORE PS NEEDED- 2 groups of different people may be less ethical and harder to find, also time consuming.
Repeated measures
Using same ps in each condition of experiment
Strengths of RMD
-ELIMINATES INDIVIDUAL DIFFERENCES- participant variables like intelligence.
-FEWER PS USED- good when ps are hard to find.
Weaknesses of RMD
-ORDER EFFECTS- fatigue & practice can distort results
-EXTRANEOUS VARIABLES
-INCREASED EXPOSURE TO DEMAND CHARACTERISTICS- ps see experimental task more than one time.
Matched pairs design
Using similar, but different, ps in each condition, such as twins, match ps on any important characteristics that may affect performance.
Strengths of Matched
-CONTROLS FOR INDIVIDUAL DIFFERENCES- they will have been carefully matched
-ORDER EFFECTS & DEMAND CHARACTERISTICS LESS OF AN ISSUE- each ps only takes part in one condition, unlike repeated measures.
Weaknesses of Matched
-INDIVIDUAL DIFFERENCES CAN NEVER BE PERFECTLY MATCHED
-DIFFICULT to match subjects
-TIME CONSUMING to find match, may not even be possible.
Counterbalancing
Overcomes problems of order effects.
Used for Repeated measures design.
-Alternating the order of ps doing conditions to average out order effects.
- AB – BA
(Half ps do condition A then B , other half do condition B then A)
Single blind procedure
Overcomes problems of demand characteristics.
-Ps unaware of aims and/or which condition they’re in.
Double blind procedure
Protects against both demand characteristics and experimenter bias.
-Ensures neither the researcher nor ps are aware of condition individual is in.
Extraneous variables
Can affect the DV (what is measured) and need to be controlled for.
-These are other factors apart from the IV that can affect outcome of an experiment (the DV).
2 main types of extraneous variables:
Situational variables
Participant variables
Situational variables
Outside influences on experiment, such as time of day, weather, noise, room experiment is in etc…
Order effects such as practice/fatigue occur when ps is asked to undertake task more than once (RMD)
How to control situational variables
1) STANDARDISATION; all instructions given, procedures followed, scoring techniques and environment must be identical for all ps tested.
2) COUNTERBALANCING; changes to the order of tasks for each ps, or use of ABBA technique. (controls for order effects)
3) RANDOMISATION; order of tasks, presentation of data is decided randomly to control for order effects.
Participant variables
Individual differences between ps such as levels of intelligence, age, gender, social class etc..
-Researcher cannot fully control these, but they can carefully select ps to reduce them.
RMD get rid of participant variables, but lead to order effects.
Matched pairs minimise participant variables but some differences still exist.
Aim
Statement of what is going to be studied- NOT a prediction of expected findings, does NOT need operationalising.
Hypotheses
Statement/prediction of what results expected to find after experiment.
A good hypotheses is:
-short
-clear
-IV identified (what you change)
-DV identified and measurable (what you measure)
Alternative hypothesis/ experimental hypothesis
States something IS going to happen.
Null hypothesis
Prediction that NO effect will be found in research.
No effect due to IV.
“no difference between…”
Experimental hypothesis- One tailed (directional)
Predicts the results will go in one certain direction.
Uses precise words such as; faster, slower, bigger, smaller, more, less.
Experimental hypothesis-
Two tailed (non-directional)
Predicts a change but doe NOT specify a direction.
Uses non-specific words like; effect, change, difference.
Predicts results will go in either direction.
E.g Alcohol will affect reaction times.
Operationalisation
Specifying a set of operations/behaviours that can be measured.
Need to show your variables are measurable.
Identify and describe IV and DV, what is meant by each variable?, what does “work better” mean?
Operationalise IV
How are you manipulating it?
Operationalise DV
How are you measuring it?
Different kinds of experiments
Lab experiment
Field experiment
Quasi/Natural experiment
Lab experiment
Researcher has strict control over variables, uses standardised procedures in controlled environment.
IV is manipulated.
Strengths of Lab
-Strict control over variables, manipulation of IV indicate cause + effect relationships.
-All other variables can be “hold constant” meaning increased control and accurate measurement.
-Standardised procedure means easy replication for future.
Weaknesses of Lab
-Artificial conditions= unnatural behaviour, results may lack ecological validity, not true to real life.
-Some situations cannot be created in a lab E.g wanting to study why people commit suicide.
Field experiment
Takes place in ps natural environment, unaware of being in an experiment, researcher manipulates IV without ps knowing.
Strengths of Field
-High in ecological validity due to natural surroundings.
-Demand characteristics less likely as people are unaware of research aim.
Weaknesses of Field
-Lack of control means hard to assume variable manipulated was actually influencing behaviour (extraneous variables could have been affecting)
-Degree of secrecy/deception required, ethical issues of consent and deception, privacy.
-Hard to replicate.
Natural/Quasi experiment
Researcher makes use of naturally occurring variables.
IV is naturally occurring. e.g age, gender, job
-Not a TRUE experiment as IV cannot be manipulated as it occurs naturally.
Strengths of Quasi
-Can investigate areas that would otherwise be unavailable to them. e.g drug users, alcoholics, victims of abuse
…all without creating harmful situations.
-High ecological validity since change of IV is natural.
Weaknesses of Quasi
-No control over ps in terms of social setting, how they were raises, their lifestyle etc..- These may be confounding variables that influence behaviour
-Hard to replicate.
-Subject to bias if ps are aware of being studied & demand characteristics.
Reliability
The consistency of a measure.
‘Reliable’ if we get same result repeatedly.
Research method considered reliable if we can repeat it and get same results.
Test-retest reliability
Test/questionnaire administered again at different points in time to assess the consistency of a test or questionnaire overtime.
Validity
Extent to which a test measures what it claims to measure. E.g does an IQ test really measure intelligence.
When we measure behaviour in a lab are we measuring same behaviour as in real life?
Internal validity
Refers to extent to whether the IV caused the effect on DV or whether it was other factors responsible within the study.
Extraneous variables threaten validity of research.
External validity
Refers to validity of a study outside research situation and provides some idea of the extent to which findings can be generalised to other peoples lives outside of the study.
Internal validity is concerned with whether…
An extraneous or confounding variable affected results. (both affect the DV).
Demand characteristics may have altered results
Mundane realism
Affects internal validity, do the tasks given reflect tasks we do in real life?
External validity is related to…
Generalising- being able to apply/generalise findings from experiment today situations beyond particular environment.
Ecological validity (form of external validity)
Is study like real life?
Population validity
Can you generalise findings from your sample to larger group of people? (population).
2 factors which affect validity:
1) Participant awareness: Awareness factors threaten validity.
2) Experimental control:
Lack of control is a threat to validity.
Increasing validity:
1) Standardisation of procedure- make conditions same except for the IV (what you want to study).
2) Reduce extraneous variables as much as possible- So you can isolate the effect of the one thing you want to study (IV).
