Resultados

summary(lm(cars_original$dist~cars_original$speed))

ggp_original <- ggplot(cars_original,aes(speed, dist)) + 
geom_point()
plot1<-ggp_original + 
stat_smooth(method = "lm",formula = y ~ x,geom = "smooth")

summary(lm(cars_outliers$dist~cars_outliers$speed))
ggp_outlier <- ggplot(cars_outliers,aes(speed, dist)) + 
geom_point()
plot2<-ggp_outlier + stat_smooth(method = "lm",formula = y ~ x,geom = "smooth")

Call:
lm(formula = cars_original$dist ~ cars_original$speed)

Residuals:
    Min      1Q  Median      3Q     Max 
-29.069  -9.525  -2.272   9.215  43.201 

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)    
(Intercept)         -17.5791     6.7584  -2.601   0.0123 *  
cars_original$speed   3.9324     0.4155   9.464 1.49e-12 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 15.38 on 48 degrees of freedom
Multiple R-squared:  0.6511,	Adjusted R-squared:  0.6438 
F-statistic: 89.57 on 1 and 48 DF,  p-value: 1.49e-12

Call:
lm(formula = cars_outliers$dist ~ cars_outliers$speed)

Residuals:
    Min      1Q  Median      3Q     Max 
-50.425 -26.583 -11.516   4.962 137.575 

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)    
(Intercept)          -34.847     19.174  -1.817   0.0748 .  
cars_outliers$speed    5.864      1.155   5.075 5.09e-06 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 44.01 on 53 degrees of freedom
Multiple R-squared:  0.3271,	Adjusted R-squared:  0.3144 
F-statistic: 25.76 on 1 and 53 DF,  p-value: 5.089e-06

p1 <- ggplot(cars_original, aes(y = dist)) +
  geom_boxplot(fill = "skyblue", outlier.color = "red", outlier.shape = 16) +
  scale_y_continuous(limits = c(0, 210)) 

p2 <- ggplot(cars_outliers, aes(y = dist)) +
  geom_boxplot(fill = "skyblue", outlier.color = "red", outlier.shape = 16) +
  scale_y_continuous(limits = c(0, 210)) 

library(patchwork)
combined_plot <- p1 + p2 + plot_layout(ncol = 2)

# Mostrar el gráfico combinado
print(combined_plot)

par(mfrow = c(1, 2))
boxplot(cars_original$dist)
boxplot(cars_outliers$dist)
dev.off()