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In survey research, the design effect is a number that shows how well a sample of people may represent a larger group of people for a specific measure of interest (such as the mean).
Description: Extensive exposition of statistical decision theory, statistics, and decision analysis from a Bayesian standpoint. Many examples and problems come from business and economics. Importance: Greatly extended the scope of applied Bayesian statistics by using conjugate priors for exponential families. Extensive treatment of sequential ...
Taguchi realized that the best opportunity to eliminate variation of the final product quality is during the design of a product and its manufacturing process. Consequently, he developed a strategy for quality engineering that can be used in both contexts. The process has three stages: System design; Parameter (measure) design; Tolerance design
A Design of Experiments will result in a set of design points, and each design point is designed to be executed one or more times, with the number of iterations based on the required statistical significance for the experiment. Effect (of a factor): How changing the settings of a factor changes the response.
An important property of a fractional design is its resolution or ability to separate main effects and low-order interactions from one another. Formally, if the factors are binary then the resolution of the design is the minimum word length in the defining relation excluding ( I ).
Design and Analysis of Experiments. Handbook of Statistics. pp. 63– 90. Zacks, S. "Adaptive Designs for Parametric Models". Design and Analysis of Experiments. Handbook of Statistics. pp. 151– 180. Kôno, Kazumasa (1962). "Optimum designs for quadratic regression on k-cube" (PDF). Memoirs of the Faculty of Science. Kyushu University.
This is a workable experimental design, but purely from the point of view of statistical accuracy (ignoring any other factors), a better design would be to give each person one regular sole and one new sole, randomly assigning the two types to the left and right shoe of each volunteer. Such a design is called a "randomized complete block design."
The design with 7 factors was found first while looking for a design having the desired property concerning estimation variance, and then similar designs were found for other numbers of factors. Each design can be thought of as a combination of a two-level (full or fractional) factorial design with an incomplete block design. In each block, a ...