variables and experimental design Flashcards
independent variable
some aspects of the experimental situation that is manipulated by the researcher - or changes naturally- so the effect on the DV can be measured
dependent variable
the variable that is measured by the researcher
operationalisation
clearly defining variables in terms of how they can be measured
independent group design
The participants only perform in one condition of the independent variable
the performance of the two groups will then then be compared
Strength of independent groups design
-There are no order effects as participants only appear in one one condition
-The demand characteristics are eliminated as participants are less likely to guess the aims of the study
disadvantages of independent group design
-no control over participant variables =different abilities of the participants in the various conditions can causes changes to the DV
-you need more participants than other designs to gather the same amount of data
how to overcome participant variables
to deal with the problem,researchers can use random allocation =ensures that each participant has the same chance of being in one condition of the IV as another
repeated measures design
The same participants experience all conditions of the experiment
Following this, the main scores from all conditions would be compared to see if there was a difference.
Strengths of repeated measures
-controls for individual differences =researchers can be more certain the dv between the two conditions is due to the iv
-fewer participants are needed= not as time consuming finding and using the participants.
Disadvantage of repeated measures design
-order effects are presented =participants my have practiced in the first condition,which cause them to before better in second condition or participants may experience boredom in the second condition=may not do the task as well
-it is also more likely that participants will work out the aim of the study when they experience all conditions pf the experiment=participants are more likely to shoe demand characteristics
How to get rid of order effects
researchers can use counterbalancing
(half of the participants do condition A first then B, and the other half will do condition B first then A
how to get rid of demand characteristics
use a double blind procedure
(researcher +participants do not know which condition they are in
matched pairs design
participants are paired up together based on variables that has been found to have an affect on the dv
- then one participant from each pair would be allocated to a different condition of the experiment
-it takes into account participant/extrainous variables
strength of matched pairs
no order effects=participants only take part in a single condition so order effects and demand characteristics are less of a problem
weakness of matched pairs design
time consuming and expensive to match the participants
-difficult to know which variables are appropriate for the participants to be matched
