Titlebook: Design and Analysis of Experiments; Angela Dean,Daniel Voss,Danel Draguljić Textbook 2017Latest edition Springer International Publishing

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Checking Model Assumptions,mation of data is suggested as well as methods for data analysis which incorporate unequal variances. The normality assumption is checked through construction of half-normal probability plots. A real experiment illustrates the techniques, and the use of SAS and R software is illustrated.

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Analysis of Covariance,es, and analysis of covariance tests and confidence interval methods for the comparison of treatment effects are also developed. The concepts introduced in this chapter are illustrated through examples and use of SAS and R software.

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Designs with Two Blocking Factors,a brief description of model assumption checking as well as an extension of the model to cover factorial experiments in row-column designs. The concepts introduced in this chapter are illustrated through examples and through the use of SAS and R software.

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Random Effects and Variance Components,riments containing one random effect and are then extended to experiments with two or more random effects. The analysis of mixed-effects models is also discussed in which both fixed effects and random effects are present. The concepts introduced in this chapter are illustrated through examples and the use of SAS and R software.

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Polynomial Regression, confidence intervals and hypothesis tests about the parameter values are developed. The investigation of linear and quadratic trends in the data via orthogonal polynomials is also discussed. The concepts introduced in this chapter are illustrated through a real experiment and with the use of SAS and R software.

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