oats.Rd
The yield of oats from a split-plot field trial using three varieties and four levels of manurial treatment. The experiment was laid out in 6 blocks of 3 main plots, each split into 4 sub-plots. The varieties were applied to the main plots and the manurial treatments to the sub-plots.
oats
This data frame contains the following columns:
B
Blocks, levels I, II, III, IV, V and VI.
V
Varieties, 3 levels.
N
Nitrogen (manurial) treatment, levels 0.0cwt, 0.2cwt, 0.4cwt and 0.6cwt, showing the application in cwt/acre.
Y
Yields in 1/4lbs per sub-plot, each of area 1/80 acre.
Yates, F. (1935) Complex experiments, Journal of the Royal Statistical Society Suppl. 2, 181--247.
Also given in Yates, F. (1970) Experimental design: Selected papers of Frank Yates, C.B.E, F.R.S. London: Griffin.
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
oats$Nf <- ordered(oats$N, levels = sort(levels(oats$N))) oats.aov <- aov(Y ~ Nf*V + Error(B/V), data = oats, qr = TRUE) summary(oats.aov)#> #> Error: B #> Df Sum Sq Mean Sq F value Pr(>F) #> Residuals 5 15875 3175 #> #> Error: B:V #> Df Sum Sq Mean Sq F value Pr(>F) #> V 2 1786 893.2 1.485 0.272 #> Residuals 10 6013 601.3 #> #> Error: Within #> Df Sum Sq Mean Sq F value Pr(>F) #> Nf 3 20020 6673 37.686 2.46e-12 *** #> Nf:V 6 322 54 0.303 0.932 #> Residuals 45 7969 177 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1#> #> Error: B #> Df Sum Sq Mean Sq F value Pr(>F) #> Residuals 5 15875 3175 #> #> Error: B:V #> Df Sum Sq Mean Sq F value Pr(>F) #> V 2 1786 893.2 1.485 0.272 #> Residuals 10 6013 601.3 #> #> Error: Within #> Df Sum Sq Mean Sq F value Pr(>F) #> Nf 3 20020 6673 37.686 2.46e-12 *** #> Nf: L 1 19536 19536 110.323 1.09e-13 *** #> Nf: Dev 2 484 242 1.367 0.265 #> Nf:V 6 322 54 0.303 0.932 #> Nf:V: L 2 168 84 0.475 0.625 #> Nf:V: Dev 4 153 38 0.217 0.928 #> Residuals 45 7969 177 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1par(mfrow = c(1,2), pty = "s") plot(fitted(oats.aov[[4]]), studres(oats.aov[[4]])) abline(h = 0, lty = 2) oats.pr <- proj(oats.aov) qqnorm(oats.pr[[4]][,"Residuals"], ylab = "Stratum 4 residuals")par(mfrow = c(1,1), pty = "m") oats.aov2 <- aov(Y ~ N + V + Error(B/V), data = oats, qr = TRUE) model.tables(oats.aov2, type = "means", se = TRUE)#> Warning: SEs for type 'means' are not yet implemented#> Tables of means #> Grand mean #> #> 103.9722 #> #> N #> N #> 0.0cwt 0.2cwt 0.4cwt 0.6cwt #> 79.39 98.89 114.22 123.39 #> #> V #> V #> Golden.rain Marvellous Victory #> 104.50 109.79 97.63