The concept of predictive power, the power of a scientific theory to generate testable predictions, differs from explanatory power and descriptive power (where phenomena that are already known are retrospectively explained or described by a given theory) in that it allows a prospective test of theoretical understanding. A classic example of the predictive power of a theory is the discovery of Neptune as a result of predictions made by mathematicians John Couch Adams and Urbain Le Verrier, based on Newton's theory of gravity. Another example of the predictive power of theories or models is Dmitri Mendeleev's use of his periodic table to predict previously undiscovered chemical elements and their properties. Though largely correct, he misjudged the relative atomic masses of tellurium and iodine. Moreover, Charles Darwin used his knowledge of evolution by natural selection to predict that since a plant (Angraecum sesquipedale) with a long spur in its flowers exists, a complementary animal with a 30 cm proboscis must also exist to feed on and pollinate it. Twenty years after his death, a form of hawk moth (Xanthopan morganii) that did just that was found. Another example of predictive power is the prediction of Einstein's theory of general relativity that the path of light would bend in the presence of a strong gravitational field. This was experimentally verified by an expedition to Sobral in Brazil and the Atlantic island of Príncipe to measure star positions during the solar eclipse of May 29, 1919, when observations made by the astrophysicist Arthur Eddington seemed to confirm Einstein's predictions. Although the measurements have been criticized by some as utilizing flawed methodology, modern reanalysis of the data suggests that Eddington's analysis of the data was accurate. Later, more precise measurements taken by radio interferometry confirmed the predictions to a high degree of accuracy. The predictive power of a theory is closely related to applications. General relativity not only predicts the bending of light but also predicts several other phenomena.

About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.