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Although breaking complex phenomena into parts is a key method in science, there are those complex phenomena (e.g. in physics, psychology, sociology, ecology) where the approach does not work. Antireductionism also arises in academic fields such as history, economics, anthropology, medicine, and biology as attempts to explain complex phenomena ...
In mathematics, a function is a rule for taking an input (in the simplest case, a number or set of numbers) [5] and providing an output (which may also be a number). [5] A symbol that stands for an arbitrary input is called an independent variable, while a symbol that stands for an arbitrary output is called a dependent variable. [6]
Stochastic independence implies mean independence, but the converse is not true.; [1] [2] moreover, mean independence implies uncorrelatedness while the converse is not true. Unlike stochastic independence and uncorrelatedness, mean independence is not symmetric: it is possible for Y {\displaystyle Y} to be mean-independent of X {\displaystyle ...
A priori knowledge is independent from any experience. Examples include mathematics, [i] tautologies and deduction from pure reason. [ii] A posteriori knowledge depends on empirical evidence. Examples include most fields of science and aspects of personal knowledge.
The history of scientific method considers changes in the methodology of scientific inquiry, not the history of science itself. The development of rules for scientific reasoning has not been straightforward; scientific method has been the subject of intense and recurring debate throughout the history of science, and eminent natural philosophers and scientists have argued for the primacy of ...
There are many philosophical and historical theories as to how scientific consensus changes over time. Because the history of scientific change is extremely complicated, and because there is a tendency to project "winners" and "losers" onto the past in relation to the current scientific consensus, it is very difficult to come up with accurate and rigorous models for scientific change. [17]
Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method.For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated.
The primary independent variable was "time". Use was made of a "covariate" consisting of yearly values of annual mean atmospheric pressure at sea level. The results showed that inclusion of the covariate allowed improved estimates of the trend against time to be obtained, compared to analyses which omitted the covariate.