Explain what is meant by confounding. What is a lurking variable? What is meant by confounding? Choose the correct answer below.
A.) Confounding in a study occurs when the effects of the explanatory variable are caused, in some part, by the effects of the response variable. When there is zero confounding in a study, the effects of the response variable are entirely caused by the effects of the explanatory variable.
B.) Confounding in a study occurs when there is little or no actual relationship between the explanatory and response variable other than random chance. This sometimes causes completely unrelated variables to appear to have a causal relationship, and can cause variables that have almost no relationship to have a very strong relationship.
C.) Confounding in a study occurs when the effects of two or more explanatory variables are not separated. Therefore, any relation that may exist between an explanatory variable and the response variable may be due to some other variable or variables not accounted for in the study.
The correct answer and explanation is :
The correct answer is:
C.) Confounding in a study occurs when the effects of two or more explanatory variables are not separated. Therefore, any relation that may exist between an explanatory variable and the response variable may be due to some other variable or variables not accounted for in the study.
Explanation:
Confounding occurs in statistical studies when the relationship between an explanatory variable (independent variable) and a response variable (dependent variable) is influenced by a third variable that is not accounted for in the analysis. This third variable is known as a confounding variable because it confounds, or mixes, the effect of the explanatory variable on the response variable, making it difficult to determine the true cause-and-effect relationship.
For example, suppose a study finds that people who drink more coffee tend to live longer. A confounding variable in this study could be physical activity. People who drink more coffee might also be more physically active, which is a factor that contributes to a longer lifespan. If researchers fail to account for this, they might mistakenly conclude that coffee directly causes longer life expectancy, when in reality, physical activity plays a crucial role.
A lurking variable is similar to a confounding variable but is not included in the study at all. It is a hidden factor that influences both the explanatory and response variables, leading to misleading conclusions. For instance, a study might show a correlation between ice cream sales and drowning incidents, but the lurking variable here is temperature—hot weather increases both ice cream sales and swimming activity, which in turn raises the risk of drowning.
To reduce confounding, researchers use randomization, control groups, and statistical adjustments to isolate the true effects of an explanatory variable on a response variable. Identifying and accounting for confounding variables is crucial for making valid scientific conclusions.