Research Methods Flashcards
What are the different Experimental designs
- Independent groups
- Repeated measures
- Matched Pairs
Evaluate Repeated measures
+ Fewer participants needed
+ Reduces individual differences effecting
- Order effects (may get bored or second time easier)
- Demand characteristics (may guess true aim)
Evaluate Matched Pairs
+ Reduces individual differences effecting
- Cant be matched exactly
- Time consuming + expensive
Evaluate independent groups
+ Order effects is not a problem
+ Cheap and easy
- Individual differences
How can you reduce individual differences in independent groups:
Random Allocation
How can you reduce order effects in repeated measures:
counterbalancing
Types of experiment:
- Lab
- Field
- Natural
- Quasi
Evaluate Lab Experiments
+ high control
therefore cause and effect is greater
+ Replicability
therefore increased validity
- Lack generalisability as unrealistic setting
- Demand characteristics as pps aware they’re being tested
Evaluate Natural Experiments
+ Gives opportunities which may not always be available
+ High external validity as natural occurrence
- Might not happen often, hard to generalise
- Cant randomly allocate as IV already exists
Evaluate Quasi Experiments
+ High control
+ Replicability
- cant randomly allocate as IV already exists
Evaluate Field Experiments
+ No demand characteristics if pps are unaware they’re being studied
+ High external validity
- Ethical issues with consent + privacy
- Hard to replicate less control
Define Lab Experiment
Takes place in controlled environment
Researcher manipulates IV and measures DV
Define Field Experiment
Takes place in natural environment
Researcher manipulates IV and measures DV
Define Quasi Experiment
IV not determined by anyone, just simply exists
Define Natural Experiment
Change in IV not determined by researcher, would have occurred anyway
Researcher records its effect on DV
Methods of sampling:
- Random
- Systematic
- Stratified
- Opportunity
Define Random Sampling
All members of target population have equal chance of being selected
Lottery method
Define Systematic Sampling
Every nth person selected from sampling frame
Define Stratified Sampling
Identify strata that make up population
Proportions needed worked out
Pps randomly selected
Define Opportunity Sampling
Researcher takes anyone who is willing and available
Define Volunteer Sampling
Volunteer selects themselves to take part in sample
Evaluate Random Sampling:
+ Free from researcher bias
- May be difficult to obtain list of whole target population
- Sample could still be unrepresentative
Evaluate Systematic Sampling:
+ Avoids researcher bias
+ Fairly representative
Evaluate Stratified Sampling:
+ Avoids researcher bias
+ Representative sample
- Complete representation isn’t possible as not all stratas can be represented
