Contents
What are the three general ways of controlling extraneous variables?
Methods to Control Extraneous Variables
- Randomization: In this approach, treatments are randomly assigned to the experimental groups.
- Matching: Another important technique is to match the different groups of confounding variables.
What type of sample will be best to control for extraneous variables?
As discussed previously, random sampling is often the best approach to obtain a representative sample. Random sampling not only controls several extraneous variables, it also allows us to generalize to a given population (increases external validity).
What is statistical control of extraneous variables?
Statistically controlling for extraneous variables is an option for removing the influence of the variable on the study of program results. Evaluators need to collect data on the extraneous variables, as well as the independent and dependent variables for analysis.
What is an extraneous variable in psychology example?
For example, if a participant is taking a test in a chilly room, the temperature would be considered an extraneous variable. Some participants may not be affected by the cold, but others might be distracted or annoyed by the temperature of the room.
What are the ways of controlling extraneous variables?
One way to control extraneous variables is with random sampling. Random sampling does not eliminate any extraneous variable, it only ensures it is equal between all groups. If random sampling isn’t used, the effect that an extraneous variable can have on the study results become a lot more of a concern.
What are the types of extraneous variables?
There are four types of extraneous variables:
- Situational Variables. These are aspects of the environment that might affect the participant’s behavior, e.g. noise, temperature, lighting conditions, etc.
- Participant / Person Variable.
- Experimenter / Investigator Effects.
- Demand Characteristics.
What are extraneous variables and how can you control it?
An extraneous variable is eliminated, for example, if background noise that might reduce the audibility of speech is removed. Unknown extraneous variables can be controlled by randomization. Randomization ensures that the expected values of the extraneous variables are identical under different conditions.
What are the types of variables in psychology?
Types of Variable
- Qualitative Variables.
- Quantitative Variables.
- Discrete Variable.
- Continuous Variable.
- Dependent Variables.
- Independent Variables.
- Background Variable.
- Moderating Variable.
How can variables be controlled?
Variables may be controlled directly by holding them constant throughout a study (e.g., by controlling the room temperature in an experiment), or they may be controlled indirectly through methods like randomization or statistical control (e.g., to account for participant characteristics like age in statistical tests).
What does it mean to control an extraneous variable?
The researcher wants to make sure that it is the manipulation of the independent variable that has an effect on the dependent variable. Hence, all the other variables that could affect the dependent variable to change must be controlled. These other variables are called extraneous or confounding variables.
What makes an experiment an extraneous variable in psychology?
As much as possible, researchers will recruit participants the same way, conduct the experiments in the same setting, and offer the same rewards for participation in the study. They will also give participants the same explanations and give similar feedback once the experiment is over.
Why do we need control in a controlled experiment?
The researcher wants to make sure that it is the manipulation of the independent variable that has changed the changes in the dependent variable. Hence, all the other variables that could affect the dependent variable to change must be controlled. These other variables are called extraneous or confounding variables.
Which is the best way to control confounding effects?
A Confounder is a variable whose presence affects the variables being studied so that the results do not reflect the actual relationship. There are various ways to exclude or control confounding variables including Randomization, Restriction and Matching.