Regression and Analysis of Variance
Preface
1
Day 1 (June 1)
1.1
Welcome
1.2
Course format
1.3
First journal
1.4
Intro to statistical modelling
2
Day 2 (June 2)
2.1
Announcements
2.2
Intro to statistical modelling: retirment example
3
Day 3 (June 3)
3.1
Announcements
3.2
Intro to statistical modelling: retirment example
3.3
Intro to statistical modelling: human movement
4
Day 4 (June 4)
4.1
Announcements
4.2
Intro to statistical modelling: human movement
5
Day 5 (June 5)
5.1
Announcements
5.2
Intro to statistical modelling: human movement
6
Day 6 (June 8)
6.1
Announcements
6.2
Matrix algebra
6.3
Introduction to linear models
6.4
Estimation
6.5
Loss function approach
7
Day 7 (June 9)
7.1
Announcements
8
Day 8 (June 10)
8.1
Announcements
8.2
Introduction to linear models
8.3
Estimation
8.4
Loss function approach
9
Day 9 (June 11)
9.1
Announcements
9.2
Estimation
9.3
Loss function approach
9.4
Maximum Likelihood Estimation
10
Day 10 (June 12)
10.1
Announcements
10.2
Loss function approach
11
Day 11 (June 15)
11.1
Announcements
11.2
Maximum Likelihood Estimation
11.3
Confidence intervals for paramters
12
Day 12 (June 16)
12.1
Announcements
13
Day 13 (June 17)
13.1
Announcements
13.2
Confidence intervals for paramters
13.3
Confidence intervals for derived quantities
14
Assignment 1
15
Assignment 2
16
Assignment 3
17
Final project
17.1
Grading Rubric
17.2
Examples of A and A+ quality work from a similar class
18
Calendar
19
Syllabus
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Regression and Analysis of Variance
12
Day 12 (June 16)
12.1
Announcements
Today is a in-class workday. Please work on Assignment 3 and the project proposal. I will be available during normal class and office hours. Journals are due, just like any other day.