Search results
Results From The WOW.Com Content Network
The seven basic tools of quality are a fixed set of visual exercises identified as being most helpful in troubleshooting issues related to quality. [1] They are called basic because they are suitable for people with little formal training in statistics and because they can be used to solve the vast majority of quality-related issues.
Elementary Principles in Statistical Mechanics, published in March 1902, is a work of scientific literature by Josiah Willard Gibbs which is considered to be the foundation of modern statistical mechanics. Its full title was Elementary Principles in Statistical Mechanics, developed with especial reference to the rational foundation of ...
Elementary Principles in Statistical Mechanics, developed with especial reference to the rational foundation of thermodynamics. New York: Charles Scribner's Sons . Sommerfeld, Arnold ; ed: F. Bopp, J. Meixner (1952).
The Foundations of Statistics are the mathematical and philosophical bases for statistical methods. These bases are the theoretical frameworks that ground and justify methods of statistical inference , estimation , hypothesis testing , uncertainty quantification , and the interpretation of statistical conclusions.
In statistics, efficiency is a measure of quality of an estimator, of an experimental design, [1] or of a hypothesis testing procedure. [2] Essentially, a more efficient estimator needs fewer input data or observations than a less efficient one to achieve the Cramér–Rao bound.
In multivariate statistics, exploratory factor analysis (EFA) is a statistical method used to uncover the underlying structure of a relatively large set of variables. EFA is a technique within factor analysis whose overarching goal is to identify the underlying relationships between measured variables. [ 1 ]
All classical statistical procedures are constructed using statistics which depend only on observable random vectors, whereas generalized estimators, tests, and confidence intervals used in exact statistics take advantage of the observable random vectors and the observed values both, as in the Bayesian approach but without having to treat constant parameters as random variables.
In statistical quality control, the CUSUM (or cumulative sum control chart) is a sequential analysis technique developed by E. S. Page of the University of Cambridge.It is typically used for monitoring change detection. [1]