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Informal prediction (hypothesis)[edit | edit source]
Outside the rigorous context of science, prediction is often confused with informed guess or opinion.
A prediction of this kind might be valid and useful if the predictor is a knowledgeable person in the field and is employing sound reasoning and accurate data.
Opinion Polls[edit | edit source]
Supernatural (prophesy)[edit | edit source]
Predictions have often been made, in pre-scientific times and still today, by resorting to paranormal or supernatural means, such as prophecy. Pseudoscience disciplines include water divining, astrology, numerology and fortune telling. So far none of these means of prediction have been proven under controlled conditions and are heavily criticised by scientists and skeptics.
Anticipatory science forecasts[edit | edit source]
In a scientific context, a prediction is a rigorous (often quantitative) statement forecasting what will happen under specific conditions, typically expressed in the form If A is true, then B will also be true. The scientific method is built on testing assertions which are logical consequences of scientific theories. This is done through repeatable experiments or observational studies.
A scientific theory whose assertions are not in accordance with observations and evidence will probably be rejected. For example, theories such as String theory make no testable predictions, and thus remain protosciences until testable predictions are known to the community.
Additionally, if new theories generate many new predictions, they are often highly valued, for they can be quickly and easily confirmed or falsified (see predictive power). In many scientific fields, desirable theories are those which predict a large number of events from relatively few underlying principles.
In microprocessors, branch prediction permits to avoid pipeline emptying at microcode branchings. Engineering is a field that involves predicting failure and avoiding it through component or system redundancy.
Some fields of science are notorious for the difficulty of accurate prediction and forecasting, such as software reliability, natural disasters, pandemics, demography, population dynamics and meteorology.
Example of scientific hypothesis[edit | edit source]
This proposition impelled Semmelweis to refine the factor. What was the difference between the midwives and the doctors? After more thought, Semmelweis decided that the cadavers which the student doctors were touching must be part of the factor.
What could the doctors do to avoid the factor? Semmelweis predicted that, if the doctors were to wash their hands, then the cadaver factor will be avoided.
Semmelweis therefore instructed the student doctors to wash their hands, and the women who were attended by the doctors survived. Thus his prediction was successful, and his explanation was validated.
(Semmelweis, 1861. The Etiology, Understanding, and Prophylaxis of Childbed Fever)
Other examples abound in the history of science, ranging from expected predictions which did not occur (such as the Michelson-Morley experiment) to new and radical predictions which shockingly confirmed one theory over another (such as the bending of light around the sun seen in the 1919 eclipse, a prediction of Albert Einstein's theory of General relativity).
Finance[edit | edit source]
Mathematical models of stock market behaviour are also unreliable in predicting future behaviour. Consequently, stock investors may anticipate or predict a stock market boom, or fail to anticpate or predict a stock market crash.
See also[edit | edit source]
- Academic achievement prediction
- Chaos theory
- Occupational success prediction
- Predicability (measurement)
- Prediction errors
- Prediction interval
- Regression analysis
- Self fulfilling prophecies
- Technique for Human Error Rate Prediction
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