Regression and Analysis of Variance
Preface
1
Day 1 (June 5)
1.1
Welcome and preliminaries
1.2
Assignment 1
2
Day 2 (June 6)
2.1
Announcements
2.2
Intro to statistical modelling
3
Day 3 (June 7)
3.1
Announcements
3.2
Intro to statistical modelling
3.3
Matrix algebra
3.4
Introduction to linear models
3.5
Estimation
3.6
Loss function approach
4
Day 4 (June 8)
4.1
Announcements
4.2
Matrix algebra
4.3
Introduction to linear models
4.4
Estimation
4.5
Loss function approach
5
Day 5 (June 9)
5.1
Announcements
5.2
Introduction to linear models
5.3
Estimation
6
Day 6 (June 12)
6.1
Announcements
6.2
Estimation
6.3
Loss function approach
7
Day 7 (June 13)
7.1
Announcements
7.2
Estimation
7.3
Loss function approach
8
Day 8 (June 14)
8.1
Announcements
8.2
Loss function approach
9
Day 9 (June 15)
9.1
Announcements
9.2
Loss function approach
10
Day 10 (June 16)
10.1
Announcements
10.2
Maximum Likelihood Estimation
10.3
Confidence intervals for paramters
11
Day 11 (June 19)
11.1
Announcements
11.2
Maximum Likelihood Estimation
11.3
Confidence intervals for paramters
12
Day 12 (June 20)
12.1
Announcements
12.2
Confidence intervals for paramters
12.3
Monte Carlo simulation
12.4
Understanding confidence intervals using synthetic data
12.5
Bootstrap confidence intervals
13
Day 13 (June 21)
13.1
Announcements
13.2
Understanding confidence intervals using synthetic data
14
Day 14 (June 22)
14.1
Announcements
14.2
Confidence intervals for derived quantities
15
Day 15 (June 23)
15.1
Announcements
15.2
Confidence intervals for derived quantities
15.3
Bootstrap confidence intervals
16
Day 16 (June 26)
16.1
Announcements
16.2
Bootstrap confidence intervals
16.3
Prediction
16.4
Intervals for predictions
17
Day 17 (June 27)
17.1
Announcements
17.2
Bootstrap confidence intervals
17.3
Prediction
17.4
Intervals for predictions
18
Day 18 (June 28)
18.1
Announcements
19
Day 19 (June 29)
19.1
Announcements
19.2
Regression and ANOVA
19.3
T-test
20
Day 20 (June 30)
20.1
Announcements
20.2
Regression and ANOVA
20.3
ANOVA/F-test
21
Day 21 (July 5)
21.1
Announcements
22
Day 22 (July 6)
22.1
Announcements
22.2
Regression and ANOVA
23
Day 23 (July 7)
23.1
Announcements
23.2
Regression and ANOVA
24
Day 24 (July 10)
24.1
Announcements
24.2
Model checking
25
Day 25 (July 11)
25.1
Announcements
26
Day 26 (July 12)
26.1
Announcements
26.2
Distributional assumptions
26.3
Constant variance
27
Day 27 (July 13)
27.1
Announcements
28
Day 28 (July 14)
28.1
Announcements
28.2
Constant variance
29
Day 29 (July 17)
29.1
Announcements
29.2
Collinearity
29.3
Model selection
30
Day 30 (July 18)
30.1
Announcements
31
Day 31 (July 19)
31.1
Announcements
31.2
Model selection
32
Day 32 (July 20)
32.1
Announcements
33
Day 33 (July 21)
33.1
Announcements
34
Day 34 (July 24)
34.1
Announcements
34.2
Random effects
35
Day 35 (July 25)
35.1
Announcements
35.2
Generalized linear models
36
Day 36 (July 26)
36.1
Announcements
36.2
The Bayesian Linear Model
37
Day 36 (July 27)
37.1
Announcements
37.2
Regression trees
37.3
Random forest
37.4
Generalized additive model
38
Day 36 (July 28)
38.1
Announcements
38.2
Data fusion
39
Assignment 1
40
Assignment 2
41
Assignment 2 (Guide)
42
Assignment 3
43
Assignment 3 (Guide)
44
Assignment 4
45
Final project
45.1
Grading Rubric
45.2
Examples of A and A+ quality work from a similar class
46
Peer review
Published with bookdown
Regression and Analysis of Variance
8
Day 8 (June 14)
8.1
Announcements
Questions about assignment 2
8.2
Loss function approach
Finish up live example from yesterday
Live example
Research publication
Data
R Script