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Data often are missing in research in economics, sociology, and political science because governments or private entities choose not to, or fail to, report critical statistics, [1] or because the information is not available. Sometimes missing values are caused by the researcher—for example, when data collection is done improperly or mistakes ...
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. One form is the appropriation of ...
Another key example of observer bias is a 1963 study, "Psychology of the Scientist: V. Three Experiments in Experimenter Bias", [9] published by researchers Robert Rosenthal and Kermit L. Fode at the University of North Dakota. In this study, Rosenthal and Fode gave a group of twelve psychology students a total of sixty rats to run in some ...
Random errors are errors in measurement that lead to measurable values being inconsistent when repeated measurements of a constant attribute or quantity are taken. Random errors create measurement uncertainty. Systematic errors are errors that are not determined by chance but are introduced by repeatable processes inherent to the system. [3]
How, then, can data ever be sufficient to prove a theory? This is the " epistemological problem of the indeterminacy of data to theory". The poverty of the stimulus argument and W.V.O. Quine 's 1960 'Gavagai' example are perhaps the most commented variants of the epistemological problem of the indeterminacy of data to theory.
HARKing (hypothesizing after the results are known) is an acronym coined by social psychologist Norbert Kerr [1] that refers to the questionable research practice of "presenting a post hoc hypothesis in the introduction of a research report as if it were an a priori hypothesis".
Some also create new terms without substantially changing the definitions of uncertainty or risk. For example, surprisal is a variation on uncertainty sometimes used in information theory. But outside of the more mathematical uses of the term, usage may vary widely.
Producing the best available information from uncertain data remains the goal of researchers, tool-builders, and analysts in industry, academia and government. Their domains include data mining, cognitive psychology and visualization, probability and statistics, etc. Abductive reasoning is an earlier concept with similarities to ACH.