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In statistical hypothesis testing, a type I error, or a false positive, is the rejection of the null hypothesis when it is actually true. A type II error, or a false negative, is the failure to reject a null hypothesis that is actually false. [1] Type I error: an innocent person may be convicted. Type II error: a guilty person may be not convicted.
A notable result of Engineering and Scientific errors that occurred in history is the Chernobyl disaster of 1986, which caused a nuclear meltdown in the City of Chernobyl in present-day Ukraine, and is used as a case study in many Engineering/Science research [7]
In statistical hypothesis testing, there are various notions of so-called type III errors (or errors of the third kind), and sometimes type IV errors or higher, by analogy with the type I and type II errors of Jerzy Neyman and Egon Pearson. Fundamentally, type III errors occur when researchers provide the right answer to the wrong question, i.e ...
Note that, because of the definition of the sample mean, the sum of the residuals within a random sample is necessarily zero, and thus the residuals are necessarily not independent. The statistical errors, on the other hand, are independent, and their sum within the random sample is almost surely not zero.
The study of learners' errors has been the main area of investigation by linguists in the history of second-language acquisition research. [2] In prescriptivist contexts, the terms "error" and "mistake" are also used to describe usages that are considered non-standard or otherwise discouraged normatively. [3]
Falsification is manipulating research materials, equipment, or processes or changing or omitting data or results such that the research is not accurately represented in the research record. Plagiarism is the appropriation of another person's ideas, processes, results, or words without giving appropriate credit.
Developmental errors: this kind of errors is somehow part of the overgeneralizations, (this later is subtitled into Natural and developmental learning stage errors), D.E are results of normal pattern of development, such as (come = comed) and (break = breaked), D.E indicates that the learner has started developing their linguistic knowledge and ...
Recall bias is a type of measurement bias, and can be a methodological issue in research involving interviews or questionnaires. In this case, it could lead to misclassification of various types of exposure . [ 2 ]