Confounding variables are extraneous variables that are related to a study's independent and dependent variables.
To be a confounder, a variable must meet two conditions: it must be associated with the outcome of the study, and it must be associated with the exposure of interest.
For example, if a study is looking at the relationship between sunburns and ice cream consumption, a confounder could be the temperature outside, as it is associated with both sunburns and ice cream consumption.
See more results on Neeva
Summaries from the best pages on the web
Confounding variables (a.k.a. confounders or confounding factors) are a type of extraneous variable that are related to a study’s independent and dependent variables . A variable must meet two conditions to be a confounder:
You collect data on sunburns and ice cream consumption. You find that higher ice cream
Confounding Variables | Definition, Examples & Controls
In statistics, a confounder (also confounding variable, confounding factor, extraneous determinant or lurking variable) is a variable that influences both the dependent variable and independent variable, causing a spurious association. Confounding is a causal concept, and as such, cannot be described in terms of correlations or associations. The existence of confounders is an important quantitative explanation why correlation does not imply causation.
Confounding - Wikipedia
Home > Examples > Science Examples > Confounding Variable Examples A confounding variable is an outside influence that changes the effect of a dependent and ...
Confounding Variable Examples
Confounding variables (aka third variables) are variables that the researcher failed to control, or eliminate, damaging the internal validity of an experiment.
Confounding Variable / Third Variable
Confounder (or Confounding variable) is one of those statistical term that confuses a lot of people. Not because it represents a confusing concept, but because ...
Confusing Statistical Terms #11: Confounder