familias <- c(0,5,10,40,100,0,2,2,30,70,80)
area <- c(0.35,0.32,0.36,0.68,0.75,0.28,0.34,0.35,0.48,0.70,0.75)
parcelas<-c(1,1,1,1,1,2,2,2,2,2,2)
sample1 <- data.frame(familias, area, parcelas)
sample1
## familias area parcelas
## 1 0 0.35 1
## 2 5 0.32 1
## 3 10 0.36 1
## 4 40 0.68 1
## 5 100 0.75 1
## 6 0 0.28 2
## 7 2 0.34 2
## 8 2 0.35 2
## 9 30 0.48 2
## 10 70 0.70 2
## 11 80 0.75 2
fit2 <- lm(familias ~ area + parcelas + area*parcelas , sample1)
summary(fit2)
##
## Call:
## lm(formula = familias ~ area + parcelas + area * parcelas, data = sample1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -25.6246 -3.5885 0.0543 4.4943 21.4833
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -62.271 37.524 -1.660 0.1410
## area 187.058 71.654 2.611 0.0349 *
## parcelas 2.657 23.082 0.115 0.9116
## area:parcelas -2.885 44.292 -0.065 0.9499
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 13.37 on 7 degrees of freedom
## Multiple R-squared: 0.9072, Adjusted R-squared: 0.8674
## F-statistic: 22.81 on 3 and 7 DF, p-value: 0.0005462
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 3.5.3
p<-ggplot(sample1,aes(area,familias,group=parcelas,color=parcelas))
p + geom_smooth(method=lm, se=F)+theme(legend.position = "top")+stat_smooth(method=lm, level=0.95)
