Comparación de dos o má tratamientos
Fuentes de varibailidad: los tratamientos y el error aleatorio
variable respuesta - aceite esencial de limonaria (AEL)
Factor - Fertilización (Control, Fertilizante foliar, Triple 15 (granular))
Unidad experimental - Parcela de 3m^2
Unidad de observación - cuadrado de 0.5m^2
Exploratorio - herramientas de estadística descriptiva
Descriptivo - (Posterior a exploratorio): Medir, Tabular y Graficar
Análisis inferencial - Utilizar las pruebas de hipótesis: intervalos de confianza o pruebas, para hacer generalizaciones
set.seed(123) # Cada quien debería usar su semilla
AEL = c(rnorm(16, 6, 0.3), rnorm(16, 8, 0.3), rnorm(16, 7.5, 0.3))
fert= gl(3,16,48,c("C", "FF", "T15"))
df = data.frame(AEL, fert);df## AEL fert
## 1 5.831857 C
## 2 5.930947 C
## 3 6.467612 C
## 4 6.021153 C
## 5 6.038786 C
## 6 6.514519 C
## 7 6.138275 C
## 8 5.620482 C
## 9 5.793944 C
## 10 5.866301 C
## 11 6.367225 C
## 12 6.107944 C
## 13 6.120231 C
## 14 6.033205 C
## 15 5.833248 C
## 16 6.536074 C
## 17 8.149355 FF
## 18 7.410015 FF
## 19 8.210407 FF
## 20 7.858163 FF
## 21 7.679653 FF
## 22 7.934608 FF
## 23 7.692199 FF
## 24 7.781333 FF
## 25 7.812488 FF
## 26 7.493992 FF
## 27 8.251336 FF
## 28 8.046012 FF
## 29 7.658559 FF
## 30 8.376144 FF
## 31 8.127939 FF
## 32 7.911479 FF
## 33 7.768538 T15
## 34 7.763440 T15
## 35 7.746474 T15
## 36 7.706592 T15
## 37 7.666175 T15
## 38 7.481426 T15
## 39 7.408211 T15
## 40 7.385859 T15
## 41 7.291588 T15
## 42 7.437625 T15
## 43 7.120381 T15
## 44 8.150687 T15
## 45 7.862389 T15
## 46 7.163067 T15
## 47 7.379135 T15
## 48 7.360003 T15
# 5.831857 -> 5.637880 Cambióset.seed(123)
muestra = sample(df$fert, replace = FALSE);muestra## [1] FF C C C T15 T15 T15 T15 FF FF FF C T15 FF C FF T15 C T15
## [20] C C T15 FF C T15 FF C T15 C T15 T15 C FF T15 FF FF C FF
## [39] T15 FF FF FF C C C T15 FF T15
## Levels: C FF T15
grilla = expand.grid(x = 1:6,
y = 1:8)
plot(grilla, pch = 0, cex = 1.2)
grid(6,8, col = "blue")
text(grilla$x - 0.13, grilla$y,muestra, cex = 0.48)Medir
Tabular
Graficar
describeBy(df$AEL, df$fert)##
## Descriptive statistics by group
## group: C
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 16 6.08 0.27 6.04 6.08 0.28 5.62 6.54 0.92 0.33 -1.1 0.07
## ------------------------------------------------------------
## group: FF
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 16 7.9 0.28 7.88 7.9 0.32 7.41 8.38 0.97 -0.02 -1.17 0.07
## ------------------------------------------------------------
## group: T15
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 16 7.54 0.28 7.46 7.53 0.34 7.12 8.15 1.03 0.37 -0.76 0.07
boxplot(df$AEL ~ df$fert, boxlwd = 3, boxcol = 2, col = c("darkolivegreen1", "darkolivegreen2", "darkolivegreen3"), main = "Diagrama de cajas")
points(x = c(1,2,3), y = tapply(df$AEL, df$fert, mean), col = "#FF6A6A", pch = 16, cex = 1.1)cols <- c("#76EE00", "darkolivegreen3", "#008B00")
# Density areas without lines
ggplot(df, aes(x = AEL, fill = fert)) +
geom_density(alpha = 0.7) +
xlim(5,9) +
scale_fill_manual(values = cols)medias = tapply(df$AEL, df$fert, mean)
medias## C FF T15
## 6.076363 7.899605 7.543224
delta_FF_C = medias[2] - medias[1]
delta_FF_C## FF
## 1.823242
deltaR_FF_C = 100* (medias[2] - medias[1])/medias[1]
deltaR_FF_C## FF
## 30.00549
delta_T15_C = medias[3] - medias[1]
delta_T15_C## T15
## 1.466862
deltaR_T15_C = 100* (medias[3] - medias[1])/medias[1]
deltaR_T15_C## T15
## 24.14046
delta_T15FF_C = medias[2] - medias[3]
delta_T15FF_C## FF
## 0.3563806
deltaR_T15FF_C = 100* (medias[2] - medias[3])/medias[3]
deltaR_T15FF_C## FF
## 4.724513
NOTA: Tener NO solo en consideración los resultados estadísticos