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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.
Your first task is to realize two additional data generation functions. Firstly, extend the system to generate random integral numbers based on normal distribution. You need to stu
Convex hull trimming : A procedure which can be applied to the set of bivariate data to permit robust estimation of the Pearson's product moment correlation coef?cient. The points
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The graph for Partial Autocorrelation Function for RES1 shows that there is no autocorrelation even though there are alternating spikes because they fall inside the 5% significance
Component bar chart : A bar chart which shows the component parts of the aggregate represented by the whole length of the bar. The component parts are shown as the sectors of bar w
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Graduation is the term is employed most often in the application of the actuarial statistics to denote procedures by which the set or group of observed probabilities is adjusted t
Intervention analysis in time series : The extension of the autoregressive integrated moving average models applied to time series permitting for the study of the magnitude and str
Artificial neural network : A mathematical arrangement modelled on the human neural network and designed to attack various statistical problems, particularly in the region of patte
how to find the PDF and CDF of a gamma random variable with given equation?
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