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1. Business Example
🔹 Study:
“Advertising increases sales”
Extraneous Variables:
These may affect sales, but if controlled, they won’t distort results.
Confounding Variable:
If ads are run along with heavy discounts, then:
2. Psychology Example
🔹 Study:
“Listening to music improves concentration”
Extraneous Variables:
Confounding Variable:
If:
Then performance improves not because of music, but because tasks were easier
👉 Task difficulty becomes a confounding variable
3. Medical Example
🔹 Study:
“Exercise reduces weight”
Extraneous Variables:
Confounding Variable:
If people who exercise also eat healthy food:
4. Education Example
🔹 Study:
“Online learning improves student performance”
Extraneous Variables:
Confounding Variable:
If highly motivated students prefer online learning:
🔥 Final Understanding Trick
Think like this:
Dear SirBased on my understanding, it is helpful to distinguish between the two terms:It is extraneous variables and confounding relationships.An extraneous variable is a third variable that affects the relationship between two primary variables. To address this, we typically measure the third variable as a control variable and attempt to remove its influence using statistical techniques such as partial correlation or hierarchical regression.If the effect cannot be successfully removed, the resulting relationship is considered a confounding relation due to the remaining influence of the extraneous variable.Excerpt from the book of Research Methodology by CR Kothari
<image.png>Best wishesNeeraj
"According to Laerd Dissertation, a variable becomes confounding when it changes systematically alongside the variables being studied, offering an alternative explanation for the results and directly threatening the internal validity of the experiment. In other words, a confounding variable doesn’t just add random noise — it creates a false or distorted picture of the relationship between the IV and DV."
"The distinction is important. As Scribbr clarifies, a confounding variable is a specific type of extraneous variable that is also related to the independent variable itself. A simple extraneous variable might affect the dependent variable; a confounding variable does that and correlates with the independent variable — making it very hard to separate cause from effect."
If Extraneous variable (EV) changes along with your IV, it becomes a confounder as EV provides an alternative explanation for results.
It also leads to over estimation / underestimation depending on the way the EV relates to the IV.
Regards
Sunil
"