x = c(1, 1, 2, 2, 3, 3.5, 4, 4.5, 5.2, 6, 6.5, 7, 7, 8, 8.5, 9, 9.5)
y1 = rnorm(17, 2, 0.5)
y = x * y1
plot(x, y)
abline(lm(y ~ x))

lm( y ~ x)
summary( lm( y ~ x ))

lm.result = simple.lm(x,y)

install.packages("UsingR")
library("UsingR")

## library("UsingR", lib.loc="C:/Users/jacobson/Documents/R/win-library/2.15")

summary(lm.result)

lm.result$coefficients

coef(lm.result)

plot(lm.result)
b1 = (coef(lm.result))[['x']]

z <- fitted(lm.result)

z <- fitted(lm.result)
xy <- data.frame(x, y, z)

plot(x, y)
predict(lm.result, data.frame(x = c(4, 12)))
## 1         2 
## 8.316998 28.302175 

> xy <- data.frame(x, y)
> xy
x         y
1  1.0  3.143263
2  1.0  1.916177
3  2.0  4.339275
4  2.0  3.542766
5  3.0  5.343987
6  3.5  6.161855
7  4.0  9.851154
8  4.5 10.270145
9  5.2  5.803766
10 6.0  9.951594
11 6.5 15.712097
12 7.0 10.906188
13 7.0 13.556769
14 8.0 21.904011
15 8.5 20.557237
16 9.0 24.331599
17 9.5 23.310576