set.seed(101)
x <- rnorm(400, 100, 10)
x
y <- 1.4*x + 2 + rnorm(400, 0, 4)
y
df <- data.frame(x,y)
# density graph
ggplot(data=df, aes(y)) + 
  geom_histogram() + 
  geom_vline(aes(xintercept=mean(y)),
             color="red", linetype="dashed", size=1) +
  coord_flip()

ggplot(data=df, aes(y)) + 
  geom_density(color="blue", size=1.5) +
  geom_vline(aes(xintercept=mean(y)),
             color="red", linetype="dashed", size=1) +
  coord_flip()

ggplot(data=df, aes(x,y)) +
  geom_point(color="blue", siz=1.5, pch=1.5) +
  stat_smooth(method = "lm",
              formula = y ~ x,
              geom = "smooth", color="red", size=1)


set.seed(401)
sn <- 25
x <- rnorm(sn, 100, 10)
x
y <- 1.4 * x + 2 + rnorm(sn, 0, 10)
y
df <- data.frame(x, y)
# density graph
ggplot(data=df, aes(y)) + 
  geom_histogram() + 
  geom_vline(aes(xintercept=mean(y)),
             color="red", linetype="dashed", size=1) +
  coord_flip()

ggplot(data=df, aes(y)) + 
  geom_density(color="blue", size=1.5) +
  geom_vline(aes(xintercept=mean(y)),
             color="red", linetype="dashed", size=1) +
  coord_flip()

lm.mod <- lm(y~x, data=df)
summary(lm.mod)
str(lm.mod)
inc.y <- lm.mod$coefficients[1]
slope.x <- lm.mod$coefficients[2]
inc.y
slope.x

ggplot(data=df, aes(x,y)) +
  geom_point(color="blue", size=1.5, pch=1.5) +
  geom_hline(aes(yintercept=mean(y))) +
  geom_abline(intercept=inc.y, slope=slope.x)


ggplot(data=df, aes(x,y)) +
  geom_point(color="blue", size=2.5, pch=2) +
  geom_hline(aes(yintercept=mean(y)), size=1.5, color="red") +
  geom_abline(intercept=inc.y, slope=slope.x, size=1.5, color="darkgreen")