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  2. Confounding - Wikipedia

    en.wikipedia.org/wiki/Confounding

    The confounding variable makes the results of the analysis unreliable. It is quite likely that we are just measuring the fact that highway driving results in better fuel economy than city driving. In statistics terms, the make of the truck is the independent variable, the fuel economy (MPG) is the dependent variable and the amount of city ...

  3. Spurious relationship - Wikipedia

    en.wikipedia.org/wiki/Spurious_relationship

    In statistics, a spurious relationship or spurious correlation [1] [2] is a mathematical relationship in which two or more events or variables are associated but not causally related, due to either coincidence or the presence of a certain third, unseen factor (referred to as a "common response variable", "confounding factor", or "lurking ...

  4. Simpson's paradox - Wikipedia

    en.wikipedia.org/wiki/Simpson's_paradox

    In this example, the "lurking" variable (or confounding variable) causing the paradox is the size of the stones, which was not previously known to researchers to be important until its effects were included. [citation needed] Which treatment is considered better is determined by which success ratio (successes/total) is larger.

  5. Correlation does not imply causation - Wikipedia

    en.wikipedia.org/wiki/Correlation_does_not_imply...

    All of those examples deal with a lurking variable, which is simply a hidden third variable that affects both of the variables observed to be correlated. That third variable is also known as a confounding variable, with the slight difference that confounding variables need not be hidden and may thus be corrected for in an analysis. Note that ...

  6. Blocking (statistics) - Wikipedia

    en.wikipedia.org/wiki/Blocking_(statistics)

    In the examples listed above, a nuisance variable is a variable that is not the primary focus of the study but can affect the outcomes of the experiment. [3] They are considered potential sources of variability that, if not controlled or accounted for, may confound the interpretation between the independent and dependent variables .

  7. Controlling for a variable - Wikipedia

    en.wikipedia.org/wiki/Controlling_for_a_variable

    The variables made to remain constant during an experiment are referred to as control variables. For example, if an outdoor experiment were to be conducted to compare how different wing designs of a paper airplane (the independent variable) affect how far it can fly (the dependent variable), one would want to ensure that the experiment is ...

  8. 10 Things You Should Never Pay For - AOL

    www.aol.com/10-things-never-pay-140000055.html

    1. A Credit Report. Don’t fall for pricey credit check and monitoring services. By law, you’re entitled to one free credit report every year from each of the three major bureaus (Equifax ...

  9. Statistics - Wikipedia

    en.wikipedia.org/wiki/Statistics

    The correlation phenomena could be caused by a third, previously unconsidered phenomenon, called a lurking variable or confounding variable. For this reason, there is no way to immediately infer the existence of a causal relationship between the two variables.