Experiments Flashcards
What is a Laboratory Experiment?
Highly Controlled and Artificial
What is a Field Experiment?
Controlled Variables in a natural/realistic environment
What is a Quasi(Natural) Experiment?
No control over the independent variable- it’s naturally occurring. e.g gender- no direct control.
Strengths of Lab Experiment…
- Ensures that the variable manipulated is the only thing affecting the behaviour
- Easy to replicate
- Can show cause and effect
Weaknesses of Lab Experiment…
- Less Ecological Validity
- Demand characteristics
- Ethics
Strengths of Field Experiment….
- More Ecological Validity
- Less demand characteristics
Weaknesses of Field Experiment ….
- Variable manipulated may be affected by something else like the situation or participants
- Difficult to replicate
Strengths of Quasi Experiment…
- Allows the study of the effects of the variables psychologists can’t manipulate or change on behaviour
- Can show cause and effect
Weaknesses of Quasi Experiment…
- No control over participants- may be confounding variables which influence behaviour
- Not easy to replicate
What is the Independent Variable…
Thing you change
What is the Dependent Variable…
Thing you measure
What is Validity?
Measure of how well a test measures what it claims to measure
What is a Confounding Variable?
Something affecting your results (the DV) that is not spotted by the experimenter
What are Participant Variables?
Changes from the people doing the test (tired or bored)
What are Situational Variables?
- Something about the situation that affects DV
- Changes in where the test is (noise, temperature, time of day)
What are Experimenter Variables?
Changes from the experimenter (tone of voice, body language)
What is an Extraneous Variable?
A variable that could affect the DV but has been controlled for so it doesn’t become confounding and affect the results (validity)
What is Experimental Design?
How you put people into groups and run the experiment
What is Independent Measures Design?
Participants take part in one condition (2 groups)
What is Repeated Measures Design?
Participants take part in both conditions
What is Matched Pairs Design?
Participants are matched in each condition for characterstics that may affect their performance- makes it similar
What are Individual Differences?
Differences between people (participant variables)
What are Demand Characteristics?
People behave accordingly to the aim
What are Order Effects?
Caused by repeated tests (situational variable)
Strengths of Independent Measures Design?
- Only in one condition- fewer situational variables such as demand characteristics- increases validity
- If someone drops out you can find someone else- only one piece of data
Weaknesses of Independent Measures Design?
- Participant Variables decrease validity
- Twice as many people needed
- One group may be better than the other( individual difference- participant variables)
Strengths of Repeated Measures Design?
- Controlling Participant Variables increases validity
- See a clear difference between participants in both conditions
Weaknesses of Repeated Measures Design?
- Participants might act accordingly-order effects- this affects validity
- Two tasks must be prepared, equivalent difficulty and may be counterbalanced
- Situational Variables affects validity
- Lose 2 sets of data if someone drops out
Strengths of Matched Pairs Design?
- Less Individual Differences so less participant variables improving validity as its been controlled
- No Problems with order effects
Weaknesses of Matched Pairs Design?
- If someone drops out you have to find another mate or you risk losing 2 sets of data
- Requires work to match participants, especially on characteristics like IQ that needs testing.
What process is used to deal with Order Effects?
- ABBA counterbalances the study and controls the order of the task, whilst not affecting validity.
A-B
B-A
What is Operationalising Variables?
How you manipulate the Independent Variable
How do you write an Alternate Hypothesis ?
There will be a significant difference between…
Then the IV and DV needs to be operationalised
What is a Null Hypothesis?
Hypothesis of no effect (used for statistical testing)
How do you write a Null Hypothesis?
There will be no significant difference between…
Then the IV and DV needs to be operationalised
Any difference will be due to chance
Why do Participant Variables Occur?
Not everyone is the same. You can only limit the effect of individual differences.
How to Solve Individual Differences…
- Take a large sample so that extreme cases have less effect on the overall result
- Random Allocation- individuals with very high or low scores may be called Outliers
- Repeated Measures Design- so you can get the same participants but use them twice
How to Solve Situational Variables…
- Standardisation-All must follow exactly the same procedure: same order, timings, equipment, surroundings
- Counterbalancing(ABBA)- Half of participants do Task A followed by Task B, the remainder do it the other way round. This increases validity as the differences should balance out
How to Solve Experimenter Variables…
- Experimenter uses Standardised Instructions
- Single Blind-Participants don’t know what the study is about- increases validity but because of ethics they have to give informed consent, so lowers ethics
- Double Blind- Participants and Investigator don’t know what the study is about
What is Conformation Bias…
When the experimenter has already made their mind up. Body language or tone of voice alters their response towards participants
What is Reliability…
Can you repeat the study and get the same results- consistent
What is Inter-Rater- Reliability…
Repeat the experiment with a different person running it- should get the same results
What is Protection From Harm…
Not harming people mentally or physically
