What do confounding variables affect?

What do confounding variables affect?

A confounding variable is an outside influence that changes the effect of a dependent and independent variable. This extraneous influence is used to influence the outcome of an experimental design. Simply, a confounding variable is an extra variable entered into the equation that was not accounted for.

How can confounding variables impact the cause and effect relationship?

A confounding variable is a third variable that influences both the independent and dependent variables. If you fail to account for them, you might over- or underestimate the causal relationship between your independent and dependent variables, or even find a causal relationship where none exists.

How does confounding variable affect the validity?

Confounding variables (aka third variables) are variables that the researcher failed to control, or eliminate, damaging the internal validity of an experiment.

What is a confounding error?

Confounding is one type of systematic error that can occur in epidemiologic studies. Confounding is the distortion of the association between an exposure and health outcome by an extraneous, third variable called a confounder.

What is confounding in research?

Confounding is often referred to as a “mixing of effects”1,2 wherein the effects of the exposure under study on a given outcome are mixed in with the effects of an additional factor (or set of factors) resulting in a distortion of the true relationship.

What is a confounding variable in biology?

A confounding variable is a variable, other than the independent variable that you’re interested in, that may affect the dependent variable. This can lead to erroneous conclusions about the relationship between the independent and dependent variables.

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.

How do you prevent 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.