When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. Multivariate statistics - Wikipedia

    en.wikipedia.org/wiki/Multivariate_statistics

    Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable, i.e., multivariate random variables. Multivariate statistics concerns understanding the different aims and background of each of the different forms of multivariate analysis, and how they relate to ...

  3. Common cause and special cause (statistics) - Wikipedia

    en.wikipedia.org/wiki/Common_cause_and_special...

    The outcomes of a perfectly balanced roulette wheel are a good example of common-cause variation. Common-cause variation is the noise within the system. Walter A. Shewhart originally used the term chance cause. [1] The term common cause was coined by Harry Alpert in 1947. The Western Electric Company used the term natural pattern. [2]

  4. Causal inference - Wikipedia

    en.wikipedia.org/wiki/Causal_inference

    Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed.

  5. Causality - Wikipedia

    en.wikipedia.org/wiki/Causality

    Knowing that causation is a matter of counterfactual dependence, we may reflect on the nature of counterfactual dependence to account for the nature of causation. For example, in his paper "Counterfactual Dependence and Time's Arrow," Lewis sought to account for the time-directedness of counterfactual dependence in terms of the semantics of the ...

  6. Exploratory causal analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_causal_analysis

    Causal analysis is the field of experimental design and statistical analysis pertaining to establishing cause and effect. [1] [2] Exploratory causal analysis (ECA), also known as data causality or causal discovery [3] is the use of statistical algorithms to infer associations in observed data sets that are potentially causal under strict assumptions.

  7. Causal analysis - Wikipedia

    en.wikipedia.org/wiki/Causal_analysis

    Causal analysis is the field of experimental design and statistics pertaining to establishing cause and effect. [1] Typically it involves establishing four elements: correlation, sequence in time (that is, causes must occur before their proposed effect), a plausible physical or information-theoretical mechanism for an observed effect to follow from a possible cause, and eliminating the ...

  8. Statistics - Wikipedia

    en.wikipedia.org/wiki/Statistics

    The set of basic statistical skills (and skepticism) that people need to deal with information in their everyday lives properly is referred to as statistical literacy. There is a general perception that statistical knowledge is all-too-frequently intentionally misused by finding ways to interpret only the data that are favorable to the ...

  9. Rubin causal model - Wikipedia

    en.wikipedia.org/wiki/Rubin_causal_model

    Rubin defines a causal effect: Intuitively, the causal effect of one treatment, E, over another, C, for a particular unit and an interval of time from to is the difference between what would have happened at time if the unit had been exposed to E initiated at and what would have happened at if the unit had been exposed to C initiated at : 'If an hour ago I had taken two aspirins instead of ...