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Scheffé's method is a single-step multiple comparison procedure which applies to the set of estimates of all possible contrasts among the factor level means, not just the pairwise differences considered by the Tukey–Kramer method. It works on similar principles as the Working–Hotelling procedure for estimating mean responses in regression ...
A confidence interval for the parameter , with confidence level or coefficient , is an interval determined by random variables and with the property: The number , whose typical value is close to but not greater than 1, is sometimes given in the form (or as a percentage ), where is a small positive number, often 0.05.
A consumer confidence index (CCI) is an economic indicator published by various organizations in several countries. In simple terms, increased consumer confidence indicates economic growth in which consumers are spending money, indicating higher consumption. Decreasing consumer confidence implies slowing economic growth, and so consumers are ...
Anything above 100 represents an increase in consumer confidence. When the index dips below 100, it means that people are anxious and are likely to spend less in the near future in favor of ...
In statistics, the Lehmann–Scheffé theorem is a prominent statement, tying together the ideas of completeness, sufficiency, uniqueness, and best unbiased estimation. [1] The theorem states that any estimator that is unbiased for a given unknown quantity and that depends on the data only through a complete, sufficient statistic is the unique ...
Multiple comparisons problem. An example of coincidence produced by data dredging (uncorrected multiple comparisons) showing a correlation between the number of letters in a spelling bee's winning word and the number of people in the United States killed by venomous spiders. Given a large enough pool of variables for the same time period, it is ...
The confidence region is calculated in such a way that if a set of measurements were repeated many times and a confidence region calculated in the same way on each set of measurements, then a certain percentage of the time (e.g. 95%) the confidence region would include the point representing the "true" values of the set of variables being estimated.
In statistics, the question of checking whether a coin is fair is one whose importance lies, firstly, in providing a simple problem on which to illustrate basic ideas of statistical inference and, secondly, in providing a simple problem that can be used to compare various competing methods of statistical inference, including decision theory.