variables

• Variables


  Things that change or vary in the world, some of which may directly cause other changes
• Independent variable


  The variable that the researcher manipulates or changes in an experiment.

  The IV form the conditions of an experiment (e.g. green light v blue light)
• Dependent variable


  The variable that the researcher measures for changes in an experiment. (e.g. number of words recalled from a word list)
• Extraneous variable


  Any variable (asides from the IV) that could influence the measurement of the dependent variable. This could cause an error, potentially showing a casual relationship between the IV and DV that isn't really there, or hiding one.
• Confounding variable


  A variable other than the IV that changes systematically between the levels of IV. Meaning as you change the IV you will also change the confounding variable. This then hides the IV's true effect (or lack of an effect) on the DV as the researcher is measuring the confounding variables' influence in addition to the IV's.
• Co-variables


  Measurements that have been made that are compared to see if they are associated. In a correlational study, the two measured co-variables are assessed for a relationship.

  Positive relationship - one co-variable increases and so does the other.

  Negative relationship - one co-variable increases the measurement of the other decreases.
• Operationalise


  It is crucial that variables are operationalised, this is clearly stating exactly what the variable is and how it is to be measured. Operationalised DV's would include the measurement scale (e.g. time in seconds). IV's would clearly express each level.
• Demand characteristics


  If the participant thinks they have discovered the aim, they may alter behaviour to match what they think the researcher wants. This could be due to cues from the researcher (body language/tone of voice) or the set up makes the aim obvious.
• Participant variables


  In an independent groups design, if there are more people with relevant characteristics, prior knowledge or skills related to the task in one condition this can result in a difference in performance between conditions unrelated to the IV.
• Situational variables


  Environmental factors present in one condition but not the other condition that could reasonably lead to a change in behaviour between the conditions. This could be related to temperature, noise or visual differences.
• Order effects


  In a repeated measures design, the fact that the participant has already completed one condition can alter behaviour in the second condition. For example, performance improvement due to practice, or performance decreases due to fatigue.
• Control


  Actions taken to minimise the effect of extraneous variables on the DV.
• Control of participant variables


  Random allocation - removes potential bias in assigning more participants with relevant characteristics to one condition in an independent group design. However, more participants with relevant characteristics can end up in one group due to chance.

  Matched pairs - relevant characteristics are measured before the study, and the top two participants are randomly assigned to separate groups.
• Control of order effects


  Counter-balancing: attempts to control for order effects. This uses the ABBA format, half the participants complete condition A first and B second, and the other half of the sample start with condition B and then A. This means that order effects such as practice influence each condition equally.
• Control of situational variables


  Standardisation: any aspects of the environment that could influence the results are listed in standardised procedures. This ensures that each participant has the same experience aside from the variation in the IV
• Control of demand characteristics


  Single and double blind trials: In a single-blind trial the participant does not know the aim of the experiment.

  In a double-blind trial, both the participant and the researcher who is directly testing the participant do not know the aim of the experiment. This is an attempt to stop the researcher from influencing the participants' behaviour with their body language/tone of voice.
• Controlling extraneous variables with pilot studies and peer review


  Pilot study: can reveal unexpected extraneous variables that need to be controlled.

  Peer review - the researcher needs to show their written up study to other experts in the field as variables may be identified that have confounded the results.