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RSM is a collection of statistical techniques used to design experiments, build models, evaluate the effects of various factors and search the optimum conditions for the factors to achieve the desired responses.
RSM is a collection of statistical techniques that is useful for designing experiments, building models, evaluating the effects of different factors and searching for optimal conditions of studied factors for desirable responses (Haddar et al. 2010).
The variables that are found significant in this initial screening can be further optimized using response surface methodology (RSM) which is a collection of statistical techniques that uses design of experiments (DoE) for building models, evaluating the effects of factors and predicting optimum conditions (Abdel-Nabi et al. 1998).
Functional data analysis (FDA) is a collection of statistical techniques specifically developed to analyse curve data [ 17- 19].
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In our case, the deep fryer is a toolbox of statistical techniques.
So, what's the role of statistical techniques here?
The variety of statistical techniques used is growing.
A wide variety of statistical techniques were used.
A sub-class of statistical techniques are known by statisticians as 'clinimetric' techniques.
Among them, RSM is a collection of certain statistical techniques for designing experiments, building models, evaluating the effect of the factors and searching for optimal conditions for desirable responses.
This model is a collection of statistical and mathematical techniques that are useful for analyzing the effects of several independent variables on a response.
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