Least squares modelling (2014)
Revision as of 15:47, 11 February 2014 by Kevin Dunn (talk | contribs)
| Class date(s): | 29 January 2014 to 13 February 2014 | ||||
 (PDF)
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Course notes and slides
- Course textbook (print chapter 4)
- Slides for class
| Date | Class number | Video and audio files | Other materials | Reading (PID) | Slides | |
|---|---|---|---|---|---|---|
| 29 January | 04C | Video (119 M) | Audio (18 M) | None | Chapter 4 | Slides for class
|
| 30 January | 04D | Video (304 M) | Audio (42 M) | See the source code below | ||
| 03 February | 05A | Video (291 M) | Audio (41 M) | See the source code below | ||
| 05 February | 05B | Video (216 M) | Audio (42 M) | None | ||
| 06 February | 05C | Video (276 M) | Audio (42 M) | Practice problems (with partial solutions) | ||
| 10 February | 06A | Video (239 M) | Audio (43 M) | None | ||
Software source code
Take a look at the software tutorial, particularly steps 16 to 22.
Code used in class
Least squares demo
x <- c(10, 8, 13, 9, 11, 14, 6, 4, 12, 7, 5)
y <- c(8.04, 6.95, 7.58, 8.81, 8.33, 9.96, 7.24, 4.26, 10.84, 4.82, 5.68)
plot(x,y)
model.ls <- lm(y ~ x)
summary(model.ls)
coef(model.ls)
confint(model.ls)
names(model.ls)
model.ls$resisduals
resid(model.ls)
plot(x, y)
abline(model.ls)