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Response surface methodology (RSM): The collection of the statistical and mathematical methods useful for improving, developing, and optimizing processes with significant applications in the design, development and formulation of the new products, as well as in the improvement of the existing product designs. The extensive applications of such type of methodology are in the industrial world particularly in the situations where many input variables potentially influence some performance measure or the quality characteristic of the product or process. The basic purpose of this methodology is to model response based on the group of the experimental factors, and to determine optimal settings of the experimental factors which maximize or minimize the response. Most of the applications include fitting and checking the adequacy of the models of form. The vector β and matrix B contain parameters of the model.
Indirect least squares: An estimation technique used in the fitting of structural equation models. Commonly least squares are first used to estimate reduced form parameters. Usi
Link functions: The link function relates the linear predictor ηi to the expected value of the data. In classical linear models the mean and the linear predictor are identical
Write a c++ program to find the sum of 0.123 ? 10 3 and 0.456 ? 10 2 and write the result inthree significant digits.
Principal factor analysis is the method of factor analysis which is basically equivalent to a principal components analysis performed on reduced covariance matrix attained by repl
This term is sometimes used for the analysis of data from the clinical trial in which treatments A and B are to be compared under the suppositions that the patients remain on their
Chi-squared distribution : It is the probability distribution, f (x), of the random variable de?ned as the sum of squares of the number (v) of independent standard normal variables
Bivariate boxplot : A bivariate analogue of boxplot in which the inner area contains 50%of the data, and a 'fence' helps to identify the potential outliers. Robust methods or techn
What is statistical inference? Statistical inference can be defined as the method of drawing conclusions from data which are subject to random variations. This is based o
Genetic algorithms: The optimization events motivated by the biological analogies. The prime idea is to try to mimic the 'survival of the fittest' rule of the genetic mutation in
A test for equality of the variances of the two populations having normal distributions, based on the ratio of the variances of the sample of observations taken from each. Most fre
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