Variables

• Describe a controlled experimentSystematic manipulation of Manipulation of variables gives the controlled experiment the unique ability to find a cause-and-effect relationships between variables
• What two conditions does a controlled experiment have?

  1. Experimental condition (sometimes called the treatment condition)
  2. Control condition
• Define variable:

  Any factor (stimulus, event, quality, trait or characteristic) that can take a range of values and can be measured or manipulated in a scientific investigation
• List all the different types of variables:

  • Independent variables
  • Dependent variables
  • Extraneous variables
  • Confounding variables
  • Controlled variables
• Define the Independent variable (IV)

  Variable that researcher manipulates
• Define the dependent variable (DV)

  Outcome variable that researcher measures to determine whether manipulating the IV had an effect
• When are the IV and DV only relevant in?

  Controlled experiments
• Where is the placement on a graph of the IV and DV

  IV = horizontal axis (x-axis)

  DV = vertical axis (y-axis)
• Define an Extraneous variable (EV):

  Any variable other than the IV that may affect the DV
• Describe the impact of extraneous variables:

  Extraneous variables are unwanted that may impact the dependent variable.

  Researchers may not be aware of any EV until study is completed.
• What happens to extraneous variables once researcher controls them?

  They become controlled variables
• Explain demand characteristics:

  Participants knowledge of the aim impacts on their behaviour
• What happens when extraneous variables are not controlled?

  Can cause an confounding effect on the interpretation of results.
• Compare and contrast extraneous and confounding variables:

  Extraneous: May influence DV

  Confounding: Cause change in DV so effects may be confused with those of the IV

  Both:

  • Unwanted variable
  • Impact on ability to draw accurate conclusions and generalisations
• Define participant variables:

  Relating to the individual characteristics of participants
• Why must researcher control participant variables

  They can potentially confound results from an experiment
• How to control participant variables?

  Gather participants with similar personal characteristics, using random allocation to create equivalent groups.

  Example: motivation, age, gender, intelligence
• Define environment variables:

  Relating to the environment the study takes place in and how it affects the participants responses
• Examples of environment variables:

  Background noise, air temperature of room the test taken in, time of day
• Define researcher variables:

  Relating to the personality characteristics, appearance and conduct of the researcher that unintentionally impact participants response
• Examples of researcher variables:

  Accent, gender, attractiveness, health, age
• Define confounding variables:

  Variables that impact the DV and also have a causal or correlational relationship with the IV
• What do confounding variables do to the IV and DV?

  Alter the relationship which can complicate results making them difficult to interpret
• Why are confounding variables a major problem for the internal validity of experiment?

  Provide alternative explanation for the results
• Explain the experimenter effect:

  The expectations and behaviours of the researcher that may bias results.

  Researcher could consciously or unconsciously give away the desired outcome of the research
• Minimize the effects of EV & CV variables: Random allocation of participants

  Purpose: To ensure each participant in the sample has an equal chance of being chosen for the control group as for the experimental group
• Minimize the effects of EV & CV variables: Single blind procedure

  The experimenter is aware of the experimental conditions while the participants are unaware of them.
• Minimize the effect of EV & CV: Standardization of procedures and instructions

  Providing the same instructions to each group of participants can minimize researcher variables and experimenter effects.