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George Box. The phrase "all models are wrong" was first attributed to George Box in a 1976 paper published in the Journal of the American Statistical Association.In the paper, Box uses the phrase to refer to the limitations of models, arguing that while no model is ever completely accurate, simpler models can still provide valuable insights if applied judiciously. [2]
Statistics, in the modern sense of the word, began evolving in the 18th century in response to the novel needs of industrializing sovereign states. In early times, the meaning was restricted to information about states, particularly demographics such as population. This was later extended to include all collections of information of all types ...
Definition, limitations and context. One usable definition is: "Misuse of Statistics: Using numbers in such a manner that – either by intent or through ignorance or carelessness – the conclusions are unjustified or incorrect." [1] The "numbers" include misleading graphics discussed in other sources. The term is not commonly encountered in ...
Statistics (from German: Statistik, orig. "description of a state, a country" [1]) is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. [2] In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical ...
Grubbs's test. In statistics, Grubbs's test or the Grubbs test (named after Frank E. Grubbs, who published the test in 1950 [1]), also known as the maximum normalized residual test or extreme studentized deviate test, is a test used to detect outliers in a univariate data set assumed to come from a normally distributed population.
Secondary data. Secondary data refers to data that is collected by someone other than the primary user. [1] Common sources of secondary data for social science include censuses, information collected by government departments, organizational records and data that was originally collected for other research purposes. [2]
Heckman correction. The Heckman correction is a statistical technique to correct bias from non-randomly selected samples or otherwise incidentally truncated dependent variables, a pervasive issue in quantitative social sciences when using observational data. [1] Conceptually, this is achieved by explicitly modelling the individual sampling ...
Statistical conclusion validity is the degree to which conclusions about the relationship among variables based on the data are correct or "reasonable". This began as being solely about whether the statistical conclusion about the relationship of the variables was correct, but now there is a movement towards moving to "reasonable" conclusions that use: quantitative, statistical, and ...