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- # summary(lm(plan_new))
- # Coefficients:
- # Estimate Std. Error t value Pr(>|t|)
- # (Intercept) 72.89375 0.83076 87.743 3.64e-09 ***
- # A1 2.88125 0.83076 3.468 0.0179 *
- # B1 2.78125 0.83076 3.348 0.0204 *
- # C1 3.11875 0.83076 3.754 0.0132 *
- # D1 -1.93125 0.83076 -2.325 0.0677 .
- # A1:B1 -1.00625 0.83076 -1.211 0.2799
- # A1:C1 -0.41875 0.83076 -0.504 0.6356
- # A1:D1 -1.24375 0.83076 -1.497 0.1946
- # B1:C1 -0.26875 0.83076 -0.323 0.7594
- # B1:D1 0.73125 0.83076 0.880 0.4190
- # C1:D1 -0.03125 0.83076 -0.038 0.9714
- if(!require("qualityTools")) install.packages("qualityTools") ; library(qualityTools)
- fat_base <- fracDesign(k = 4)
- runOrd(fat_base) <- standOrd(fat_base)
- # response(fat_base) <- resp
- # paretoPlot(fat_base,
- ylim = c(0,7),
- ylab = "Standadized Effects",
- xlab = "Term",
- main = "Pareto Chart of the Standadized Effects")
- # With
- # ylim = c(0,15)
- if(!require("FrF2")) install.packages("FrF2") ; library(FrF2)
- plan.act <- FrF2(nfactors = 4,
- nruns = 16,
- randomize = FALSE)
- resp <- c(63.8, 77.6, 68.8, 76.5, 72.5, 77.2, 77.7, 84.5, 60.6, 64.9,
- 72.7, 73.3, 68.0, 76.3, 76.0, 75.9)
- plan_new <- add.response(design = plan.act, response = resp)
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