Research Methods: Experiments Flashcards
Define Experiments.
What can we show by manipulating the IV and measuring the DV?
The comparison of two conditions of the IV.
Cause and effect
What is the independent variable (IV)?
The variable that the researcher wants to test to see if it affects the outcome being measured.
What is the dependent variable (DV)?
The variable the researcher does not control or manipulate - it is simply recorded.
The DV provides data. What are three ways data can be measured?
A questionnaire, an observation, and a reading of a biological factor e.g. heart rate
What is an extraneous variable (EV)?
Anything that might possibly interfere with the experiment, a ‘nuisance’. E.g. noise, temperature, busy-ness of street, things that may vary in participants, etc.
Define Control.
Keeping things the same so they don’t interfere.
What is a confounding variable (CV)?
Something which, if you didn’t control would influence the results. It is said to ‘vary with the IV’ - it is different in each condition and therefore acts like another IV. E.g. driving experience
Define Operationalise.
To specify behaviors that can be measured or manipulated. - always be as specific as possible. Operationalising applies to both the IV and DV.
Define Hypothesis.
A clear precise testable statement stating the relationship between the variables to be investigated. Stated at the outset of any experiment or correlational study.
What do experimental hypotheses always predict?
That there will be a difference between the two conditions of the IV (on whatever is being measured).
Define Non-directional Hypothesis.
When is it used?
The direction of results is not predicted. Used when no previous research in the area. (Say that groups will differ)
Define Directional Hypothesis.
When is it used?
Predict the expected direction of the results. Only used if previous research shows the likely outcome. (Say that one group will be e.g. higher, faster, etc.)
Define Null Hypothesis.
This is the statement that there will not be a difference (just add no/not to your hypothesis).
Define Participant Variables.
Anything that may vary between participants which may affect the DV.
Define Situational Variables.
Anything in the research situation that may affect the DV.
What are some examples of Participant Variables?
Gender, ethnicity, IQ, mental health, past experiences, attention span, personality factors, wealth/socioeconomic status, parenthood and disability
Define Experimental Designs.
The 3 ways to carry out the experiment with participants. Each design controls for participant variables in some way.
What are the 3 Experimental Designs?
- Independent Groups Design
- Repeated Measures Design
- Matched Pairs Design
Describe the Independent Groups Design.
Using different participants for each condition. Participants only take part in one condition. Randomly allocating participants to groups controls participant variables to some extent.
Describe the Repeated Measures Design.
Using the same participants for each condition of the experiment. Participants take part in both conditions. This represents perfect control of participant variables as every participant appears in both groups.
Describe the Matched Pairs Design.
Using different participants but matched for each condition. Participants take part in one condition. Matched on similar characteristics that may affect the DV. You can control for some participant variables which you believe to be particularly important.
What are the strengths and weaknesses of the Independent Groups Design?
Strengths:
- no order effects (compared to repeated measures)
- less chance of demand characteristics (one condition only)
Weaknesses:
- participant variables (differ between participants)
- number of participants (need more - time + money consuming)
What are the strengths and weaknesses of the Repeated Measures Design?
Strengths:
- participant variables (fully controlled so more valid)
- number of participants (fewer so quicker and cheaper)
Weaknesses:
- possible order effects
- more chance of demand characteristics
What are the strengths and weaknesses of the Matched Pairs Design?
Strengths:
- no order effects (compared to repeated measures)
- last chance of demand characteristics (compared to repeated measures)
- participant variables (some are controlled)
Weaknesses:
- participant variables (some won’t be controlled)
- number of participants (more, and may be difficult to match them - more time + money consuming)