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Statistical proof is the rational demonstration of degree of certainty for a proposition, hypothesis or theory that is used to convince others subsequent to a statistical test of the supporting evidence and the types of inferences that can be drawn from the test scores.
JEHPS: Recent publications in the history of probability and statistics; Electronic Journ@l for History of Probability and Statistics/Journ@l Electronique d'Histoire des Probabilités et de la Statistique; Figures from the History of Probability and Statistics (Univ. of Southampton) Materials for the History of Statistics (Univ. of York)
Historical method is the collection of techniques and guidelines that historians use to research and write histories of the past. Secondary sources, primary sources and material evidence such as that derived from archaeology may all be drawn on, and the historian's skill lies in identifying these sources, evaluating their relative authority, and combining their testimony appropriately in order ...
Statistical hypothesis testing is a key technique of both frequentist inference and Bayesian inference, although the two types of inference have notable differences. Statistical hypothesis tests define a procedure that controls (fixes) the probability of incorrectly deciding that a default position (null hypothesis) is incorrect. The procedure ...
Statistics subsequently branched out into various directions, including decision theory, Bayesian statistics, exploratory data analysis, robust statistics, and non-parametric statistics. Neyman-Pearson hypothesis testing made significant contributions to decision theory, which is widely employed, particularly in statistical quality control.
JEHPS: Recent publications in the history of probability and statistics; Electronic Journ@l for History of Probability and Statistics/Journ@l Electronique d'Histoire des Probabilitéet de la Statistique; Figures from the History of Probability and Statistics (Univ. of Southampton) Probability and Statistics on the Earliest Uses Pages (Univ. of ...
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The Italian mathematician Gerolamo Cardano (1501–1576) stated without proof that the accuracies of empirical statistics tend to improve with the number of trials. [9] [3] This was then formalized as a law of large numbers. A special form of the LLN (for a binary random variable) was first proved by Jacob Bernoulli.