Diseños factoriales de 2 niveles.

#install.packages("DoE.base")
library (DoE.base)

## Loading required package: grid

## Loading required package: conf.design

## Registered S3 method overwritten by 'DoE.base':
##   method           from       
##   factorize.factor conf.design

## 
## Attaching package: 'DoE.base'

## The following objects are masked from 'package:stats':
## 
##     aov, lm

## The following object is masked from 'package:graphics':
## 
##     plot.design

## The following object is masked from 'package:base':
## 
##     lengths

factores <- list(fa=c(115,140),ra=c(150,170))
datos <- fac.design(factor.names = factores,randomize = F)

## creating full factorial with 4 runs ...

#Experimento

Y <- c(361.10,
83.48,
530.32,
310.63)

datos <- add.response(datos,Y)

#Análisis
plot(datos)

summary(lm(Y~fa+ra,datos))

## 
## Call:
## lm.default(formula = Y ~ fa + ra, data = datos)
## 
## Residuals:
##      1      2      3      4 
##  14.48 -14.48 -14.48  14.48 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)  
## (Intercept)   321.38      14.48  22.191   0.0287 *
## fa1          -124.33      14.48  -8.585   0.0738 .
## ra1            99.09      14.48   6.842   0.0924 .
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 28.97 on 1 degrees of freedom
## Multiple R-squared:  0.9918, Adjusted R-squared:  0.9753 
## F-statistic: 60.26 on 2 and 1 DF,  p-value: 0.09072

halfnormal(datos,alpha=.01)

## simulated critical values not available for all requests, used conservative ones

## no significant effects

avar <- aov(Y~fa+ra,datos)
summary (avar)

##             Df Sum Sq Mean Sq F value Pr(>F)  
## fa           1  61829   61829   73.70 0.0738 .
## ra           1  39277   39277   46.82 0.0924 .
## Residuals    1    839     839                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

library (margins)
cplot(avar)

##   xvals    yvals    upper     lower
## 1   115 346.6175 395.7821 297.45293
## 2   140  97.9625 147.1271  48.79793

#==========================
#install.packages("SixSigma")
library(SixSigma)

## Error in get(genname, envir = envir) : object 'testthat_print' not found

ss.heli()

## png 
##   2

#Buscar en el directorio de trabajo el pdf
#helicopter.pdf
#Imprimir 30 copias en papel bond normal
#Tener cinta adhesiva, tijeras y clips

R Notebook

Diseños factoriales de 2 niveles.