What is the difference between experimental and non experimental methods
Experimental - establishing cause and effect through having an IV and DV
Non experimental don’t have an IV or DV
What are some examples of experimental and non experimental methods
Non experimental:
Case study
Observation
Lab study
Correlation
Interview
Questionnaire
Experimental:
Field experiment
Natural experiment
What are the different types of experiments
Lab:
in a controlled setting where researcher controls extraneous variables. Commonly used method.
Strengths - high internal validity and cause and effect can be established. Also replicable
Weaknesses - low ecological validity (may not affect real world behaviour). Demand characteristics may be high.
Field:
In real world setting where researcher manipulates the IV.
Strengths - Higher ecological validity than lab experiments. Reduces demand characteristics.
Weaknesses - low control of extraneous variables. Replication harder. Cause and
Different types of experiments - lab
Lab - conducted in controlled setting where researcher controls extraneous variables
Commonly used method.
Strengths - high internal validility and cause and effect can be established. Replicable.
Weaknesses - Low ecological validity (may not effect real world behaviour)
Demand characteristics may be high.
Different types of experiments - field
Conducted in a real setting where researcher manipulates the IV
Strengths - higher ecological validity than lab experiments. Reduces demand characteristics.
Weaknesses- low control of extraneous variables. Replication is harder. Cause and effect is harder to establish.
Different types of experiments - natural
Natural - the IV is naturally occurring (not manipulated by experimenter)
Real world setting
Strengths - can study variables that would be impossible/ unethical to control. High ecological validility
Different experiments - quasi
Participants are grouped based on pre - existing characteristics so IV isn’t directly manipulated.
Strengths - can study real world differences
Weaknesses - random allocation isn’t possible
Independent and dependant variable
IV - the thing that I change
DV - the thing that is effected by the independent- is measured.
What is operationalsation
Making a variable measurable
What is directional and non directional hypothesis
Directional - when a clear affect/ outcome is predicted
Non-directional - when the prediction is not clear even though it is established there will be an effect.
No clear outcome, just a difference is established
Order effects
Element that can effect the experiment (e.g. practice or fatigue)
Investigator effects
Where a researchers behaviour influences or makes the data bias
Counterbalancing
To overcome order effects
Half the group does the second condition first and the other half does it in the correct order.
Pilot study
Test run/ small scale version of o.g. Study
Hawthorn effect
Behaviour of patients changing knowing they are being reserved
What is validility
Whether a measure (experiment) produces an accurate result.
Whether the observed effect is genuine and represents what is actually ‘out there’ in the real world.
What is internal validity
Wether researcher has measured what it intended to measure
External validity
Whether data can be generalised to other situations outside of the original research environment.
What are the two types of internal validity
Construct - measuring the right concept that is intended
Concurrent - whether the measure is in agreement with pre existing measures/experiments
How can you assess internal validity
Can be assessed on whether unwanted variables that could also effect experiment are successfully controlled/eliminated - the greater control of these variables, the greater the confidence in the experiment
What are the two types of external validity
Ecological - whether data is generalisable to the real world, based on the conditions research is conducted under and procedures involved
Temporal - high when research findings successfully apply across time and stay relevant in the future
How can you assess validity - 2 types
Face validity - whether the experiment measures what it’s supposed to
Concurrent validity - whether a measure is in agreement with pre existing measures that test similar concepts
How can you improve validity
Use a control group
Standardise procedures - every participant is treated the same way
Single blind study
Double blind study
How can you prove validity of a questionnaire
Incorporating a lie scale within questions in order to assess the consistency of a participants response and control effects of social desirability bias
Assuring participants data is given anonymously, so they can answer truthfully
