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  2. Spurious relationship - Wikipedia

    en.wikipedia.org/wiki/Spurious_relationship

    Graphical model: Whereas a mediator is a factor in the causal chain (top), a confounder is a spurious factor incorrectly implying causation (bottom). 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 ...

  3. Correlation does not imply causation - Wikipedia

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

    Correlations must first be confirmed as real, and every possible causative relationship must then be systematically explored. In the end, correlation alone cannot be used as evidence for a cause-and-effect relationship between a treatment and benefit, a risk factor and a disease, or a social or economic factor and various outcomes.

  4. Spurious correlation of ratios - Wikipedia

    en.wikipedia.org/wiki/Spurious_correlation_of_ratios

    The phenomenon of spurious correlation of ratios is one of the main motives for the field of compositional data analysis, which deals with the analysis of variables that carry only relative information, such as proportions, percentages and parts-per-million. [3] [4] Spurious correlation is distinct from misconceptions about correlation and ...

  5. Simpson's paradox - Wikipedia

    en.wikipedia.org/wiki/Simpson's_paradox

    Visualization of Simpson's paradox on data resembling real-world variability indicates that risk of misjudgment of true causal relationship can be hard to spot. Simpson's paradox is a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined.

  6. Confounding - Wikipedia

    en.wikipedia.org/wiki/Confounding

    Confounding is defined in terms of the data generating model. Let X be some independent variable, and Y some dependent variable.To estimate the effect of X on Y, the statistician must suppress the effects of extraneous variables that influence both X and Y.

  7. Bitcoin's 2025 Outlook Suddenly Looks Uncertain: Here's Why - AOL

    www.aol.com/bitcoins-2025-outlook-suddenly-looks...

    As 2025 approaches, Bitcoin (CRYPTO: BTC) finds itself navigating a shifting macroeconomic landscape, with fading tailwinds raising concerns about sustained momentum, according to a report. What ...

  8. Multiple comparisons problem - Wikipedia

    en.wikipedia.org/wiki/Multiple_comparisons_problem

    For example, if one test is performed at the 5% level and the corresponding null hypothesis is true, there is only a 5% risk of incorrectly rejecting the null hypothesis. However, if 100 tests are each conducted at the 5% level and all corresponding null hypotheses are true, the expected number of incorrect rejections (also known as false ...

  9. A top Fed official leans toward December rate cut but says it ...

    www.aol.com/top-fed-official-leans-toward...

    A top Federal Reserve official said Monday that he is leaning toward supporting an interest rate cut when the Fed meets in two weeks but that evidence of persistent inflation before then could ...

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