## SL Lab1 (zestaw 4)

library(ggplot2)

# PART 1 ------------------------------------------------------------------

dataset1<-part1_set04

#1
#The data is normal if the p-value is above 0.05. So we now know our variable is normally distributed.

shapiro.test(dataset1$dose)


shapiro.test(dataset1$concentration)


#2

ggplot(dataset1, aes(x=dose, y=concentration)) + geom_point()

#3
#install.packages("ggpubr")
library("ggpubr")

r = cor(dataset1$dose, dataset1$concentration, method = "pearson")

#5

#b1 = (1/(n-1))*( (sum((xi-xŚr)(yi-yŚr))) / (sd(dataset1$dose)*sd(dataset1$concentration)) ) * ()

# b1 = r*(sd(dataset1$dose)/sd(dataset1$concentration))
# b0 = mean(dataset1$dose) - b1*mean(dataset1$concentration)

b1 = r*(sd(dataset1$concentration)/sd(dataset1$dose))
b0 = mean(dataset1$concentration) - b1*mean(dataset1$dose)

lm(dataset1)

ggplot(dataset1, aes(x=dose, y=concentration)) +
  geom_point(shape=1) +
  geom_smooth(method=lm, se=FALSE)

# PART 2 ------------------------------------------------------------------