plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
Z = c(rep("Stage_0", 100), rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100))
dat = data.frame("Dosage" = X, "Weigh_Loss" = Y, Z)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample
set.seed(0)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
Z = c(rep("Stage_0", 100), rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100))
dat = data.frame("Dosage" = X, "Weigh_Loss" = Y, Z)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
View(dat)
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404, ), ]
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
sample
set.seed(0)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
Z = c(rep("Stage_0", 100), rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100))
dat = data.frame("Dosage" = X, "Weigh_Loss" = Y, "Severity" = Z)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
sample
sample
rownames(sample) = 1:nrow(sample)
sample
View(sample)
library(ggplot)
library(ggplot2)
set.seed(0)
library(ggplot2)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
Z = c(rep("Stage_0", 100), rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100))
dat = data.frame("Dosage" = X, "Weigh_Loss" = Y, "Severity" = Z)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
rownames(sample) = 1:nrow(sample)
dat %>%
ggplot(aes(Dosage, Weigh_Loss, color=Severity)) +
geom_point() +
ylab('Weight Loss')
# dat %>%
ggplot(aes(Dosage, Weigh_Loss, color=Severity)) +
geom_point() +
ylab('Weight Loss')
# dat %>%
ggplot(aes(X, Y, color=Z)) +
geom_point() +
ylab('Weight Loss')
set.seed(0)
library(ggplot2)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
Z = c(rep("Stage_0", 100), rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100))
dat = data.frame("Dosage" = X, "Weigh_Loss" = Y, "Severity" = Z)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
rownames(sample) = 1:nrow(sample)
# dat %>%
ggplot(aes(X, Y, color=Z)) +
geom_point() +
ylab('Weight Loss')
?ggplot
# dat %>%
ggplot(dat, aes(Dosage, Weigh_Loss, color=Severity)) +
geom_point() +
ylab('Weight Loss')
set.seed(0)
library(ggplot2)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
Z = c(rep("Stage_4", 100), rep("Stage_3", 100), rep("Stage_2", 100), rep("Stage_1", 100), rep("Stage_0", 100))
dat = data.frame("Dosage" = X, "Weigh_Loss" = Y, "Severity" = Z)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
rownames(sample) = 1:nrow(sample)
# dat %>%
ggplot(dat, aes(Dosage, Weigh_Loss, color=Severity)) +
geom_point() +
ylab('Weight Loss')
View(sample)
ggplot(dat, aes(Dosage, Weigh_Loss, color=Severity)) +
geom_point() +
ylab('Weight Loss')
set.seed(0)
library(ggplot2)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
Z = c(rep("Stage_4", 100), rep("Stage_3", 100), rep("Stage_2", 100), rep("Stage_1", 100), rep("Stage_0", 100))
dat = data.frame("Dosage" = X, "Weigh_Loss" = Y, "Severity" = Z)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
rownames(sample) = 1:nrow(sample)
ggplot(dat, aes(Dosage, Weigh_Loss, color=Severity)) +
geom_point()
ggplot(dat, aes(Dosage, Weigh_Loss)) +
geom_point()
ggplot(dat, aes(Dosage, Weigh_Loss, color=Severity)) +
geom_point()
set.seed(0)
library(ggplot2)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
Z = c(rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100), rep("Stage_0", 100))
dat = data.frame("Dosage" = X, "Weigh_Loss" = Y, "Severity" = Z)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
rownames(sample) = 1:nrow(sample)
ggplot(dat, aes(Dosage, Weigh_Loss)) +
geom_point()
ggplot(dat, aes(Dosage, Weigh_Loss, color=Severity)) +
geom_point()
set.seed(0)
library(ggplot2)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
Z = c(rep("Stage_0", 100), rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100))
dat = data.frame("Dosage" = X, "Weigh_Loss" = Y, "Severity" = Z)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
rownames(sample) = 1:nrow(sample)
ggplot(dat, aes(Dosage, Weigh_Loss)) +
geom_point()
ggplot(dat, aes(Dosage, Weigh_Loss, color=Severity)) +
geom_point()
set.seed(0)
library(ggplot2)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
Z = c(rep("Stage_0", 100), rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100))
dat = data.frame("Dosage" = X, "Weigh_Loss" = Y, "Severity" = Z)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
rownames(sample) = 1:nrow(sample)
ggplot(dat, aes(Dosage, Weigh_Loss)) +
geom_point()
ggplot(dat, aes(Dosage, Weigh_Loss, color=Severity)) +
geom_point() +
ylab("Weight Loss")
ggplot(dat, aes(Dosage, Weigh_Loss, color=Age)) +
geom_point() +
ylab("Weight Loss")
set.seed(0)
library(ggplot2)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
# X: treatment
# Y: outcome
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
severity = c(rep("Stage_0", 100), rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100))
age = c(rep("20-30", 100), rep("30-40", 100), rep("40-50", 100), rep("50-60", 100), rep("60-70", 100))
dat = data.frame("Dosage" = X, "Weigh_Loss" = Y,
"Severity" = severity, "Age" = age)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
rownames(sample) = 1:nrow(sample)
ggplot(dat, aes(Dosage, Weigh_Loss)) +
geom_point()
ggplot(dat, aes(Dosage, Weigh_Loss, color=Severity)) +
geom_point() +
ylab("Weight Loss")
ggplot(dat, aes(Dosage, Weigh_Loss, color=Age)) +
geom_point() +
ylab("Weight Loss")
set.seed(0)
library(ggplot2)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
# X: treatment
# Y: outcome
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
severity = c(rep("Stage_0", 100), rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100))
age =
c(rep("20-30", 100), rep("30-40", 100), rep("40-50", 100), rep("50-60", 100), rep("60-70", 100))
dat = data.frame("Dosage" = X, "Weight_Loss" = Y,
"Severity" = severity, "Age" = age)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
rownames(sample) = 1:nrow(sample)
ggplot(dat, aes(Dosage, Weigh_Loss)) +
geom_point()
ggplot(dat, aes(Dosage, Weigh_Loss, color=Severity)) +
geom_point() +
ylab("Weight Loss")
ggplot(dat, aes(Dosage, Weigh_Loss, color=Age)) +
geom_point() +
ylab("Weight Loss")
set.seed(0)
library(ggplot2)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
# X: treatment
# Y: outcome
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
severity = c(rep("Stage_0", 100), rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100))
age = c(rep("20-30", 100), rep("30-40", 100), rep("40-50", 100), rep("50-60", 100), rep("60-70", 100))
dat = data.frame("Dosage" = X, "Weight_Loss" = Y,
"Severity" = severity, "Age" = age)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
rownames(sample) = 1:nrow(sample)
ggplot(dat, aes(Dosage, Weigh_Loss)) +
geom_point()
ggplot(dat, aes(Dosage, Weigh_Loss, color=Severity)) +
geom_point() +
ylab("Weight Loss")
ggplot(dat, aes(Dosage, Weigh_Loss, color=Age)) +
geom_point() +
ylab("Weight Loss")
set.seed(0)
library(ggplot2)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
# X: treatment
# Y: outcome
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
severity = c(rep("Stage_0", 100), rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100))
age = c(rep("20-30", 100), rep("30-40", 100), rep("40-50", 100), rep("50-60", 100), rep("60-70", 100))
dat = data.frame("Dosage" = X, "Weight_Loss" = Y,
"Severity" = severity, "Age" = age)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
rownames(sample) = 1:nrow(sample)
ggplot(dat, aes(Dosage, Weigh_Loss)) +
geom_point()
ggplot(dat, aes(Dosage, Weight_Loss, color=Severity)) +
geom_point() +
ylab("Weight Loss")
ggplot(dat, aes(Dosage, Weigh_Loss, color=Age)) +
geom_point() +
ylab("Weight Loss")
set.seed(0)
library(ggplot2)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
# X: treatment
# Y: outcome
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
severity = c(rep("Stage_0", 100), rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100))
age = c(rep("20-30", 100), rep("30-40", 100), rep("40-50", 100), rep("50-60", 100), rep("60-70", 100))
dat = data.frame("Dosage" = X, "Weight_Loss" = Y,
"Severity" = severity, "Age" = age)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
rownames(sample) = 1:nrow(sample)
ggplot(dat, aes(Dosage, Weigh_Loss)) +
geom_point()
ggplot(dat, aes(Dosage, Weight_Loss, color=Severity)) +
geom_point() +
ylab("Weight Loss")
ggplot(dat, aes(Dosage, Weight_Loss, color=Age)) +
geom_point() +
ylab("Weight Loss")
set.seed(0)
library(ggplot2)
X1 = runif(100, 0, 2)
Y1 = X1*0.4 + 3 + rnorm(100, 0, 0.25)
plot(X1, Y1)
X2 = runif(100, 1, 3)
Y2 = X2*0.4 + 2 + rnorm(100, 0, 0.25)
plot(X2, Y2)
X3 = runif(100, 2, 4)
Y3 = X3*0.4 + 1 + rnorm(100, 0, 0.25)
plot(X3, Y3)
X4 = runif(100, 3, 5)
Y4 = X4*0.4 + 0 + rnorm(100, 0, 0.25)
plot(X4, Y4)
X5 = runif(100, 4, 6)
Y5 = X5*0.4 - 1 + rnorm(100, 0, 0.25)
plot(X5, Y5)
# X: treatment
# Y: outcome
X = c(X1, X2, X3, X4, X5)
Y = c(Y1, Y2, Y3, Y4, Y5)
severity = c(rep("Stage_0", 100), rep("Stage_1", 100), rep("Stage_2", 100), rep("Stage_3", 100), rep("Stage_4", 100))
age = c(rep("20-30", 100), rep("30-40", 100), rep("40-50", 100), rep("50-60", 100), rep("60-70", 100))
dat = data.frame("Dosage" = X, "Weight_Loss" = Y,
"Severity" = severity, "Age" = age)
plot(X, Y, xlab = "Dosage", ylab = "Weight Loss")
sample = dat[c(3, 4, 105, 106, 202, 203, 302, 303, 403, 404), ]
rownames(sample) = 1:nrow(sample)
ggplot(dat, aes(Dosage, Weight_Loss)) +
geom_point()
ggplot(dat, aes(Dosage, Weight_Loss, color=Severity)) +
geom_point() +
ylab("Weight Loss")
ggplot(dat, aes(Dosage, Weight_Loss, color=Age)) +
geom_point() +
ylab("Weight Loss")
setwd("~/Desktop/Algorithmic Fairness/OptimalPrediction/ICML/Sim 3_ICML")
res =read.csv("results_sim3_100boots_hybrid.csv")
apply(res, 2, mean)
