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An example of Neyman–Pearson hypothesis testing (or null hypothesis statistical significance testing) can be made by a change to the radioactive suitcase example. If the "suitcase" is actually a shielded container for the transportation of radioactive material, then a test might be used to select among three hypotheses: no radioactive source ...
For Putnam, the working hypothesis represents a practical starting point in the design of an empirical research exploration. A contrasting example of this conception of the working hypothesis is illustrated by the brain-in-a-vat thought experiment. This experiment involves confronting the global skeptic position that we, in fact, are all just ...
A research question is "a question that a research project sets out to answer". [1] Choosing a research question is an essential element of both quantitative and qualitative research . Investigation will require data collection and analysis, and the methodology for this will vary widely.
The process discourages the analyst from choosing one "likely" hypothesis and using evidence to prove its accuracy. Cognitive bias is minimized when all possible hypotheses are considered. [1] Evidence – The analyst then lists evidence and arguments (including assumptions and logical deductions) for and against each hypothesis. [1]
The consistent application by statisticians of Neyman and Pearson's convention of representing "the hypothesis to be tested" (or "the hypothesis to be nullified") with the expression H 0 has led to circumstances where many understand the term "the null hypothesis" as meaning "the nil hypothesis" – a statement that the results in question have ...
The hypothesis of Andreas Cellarius, showing the planetary motions in eccentric and epicyclical orbits. A hypothesis (pl.: hypotheses) is a proposed explanation for a phenomenon. A scientific hypothesis must be based on observations and make a testable and reproducible prediction about reality, in a process beginning with an educated guess or ...
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 ...
In 1970, L. A. Marascuilo and J. R. Levin proposed a "fourth kind of error" – a "type IV error" – which they defined in a Mosteller-like manner as being the mistake of "the incorrect interpretation of a correctly rejected hypothesis"; which, they suggested, was the equivalent of "a physician's correct diagnosis of an ailment followed by the ...