A Minimal Book Example
1
Introduction
2
Preamble
3
Aknowledgments
4
Using R
5
About regression
5.1
What is a regression?
5.2
The general linear model
6
Hands On Regression
6.1
The assumptions are on the residuals, not the data
7
Class 6 13 10 2020
7.1
Implementing a regression
7.2
Simulating regression data
7.2.1
What is the effect of increasing the error: a simulation experiment
8
Class 7 14 10 2020
8.1
Task 1
8.2
Task 2
9
Class 8 20 10 2020 - t-test and ANOVA are just linear models
9.1
The t-test
9.2
ANOVA
10
Class 9: 21 10 2020 - ANCOVA is (also) just a linear model
10.1
Common slope, different intercepts per treatment
11
Class 10: 27 10 2020
11.1
Same story, another spin
12
Class 11: 03 11 2020 ANCOVA with different slopes: interactions
12.1
About interactions
12.2
Task 1 Implementing the ANCOVA with different slopes
12.3
Task 2 Modeling a data set
13
Class 12: 04 11 2020 Interactions between continous covariates
13.1
Larger order interactions
14
Conlusion on linear regression
14.1
Conclusion
15
Class 13: 10 11 2020 Maximum likelihood and all that
15.1
Maximizing a likelihood algebraically
15.2
Numerically Maximizing a likelihood
15.3
The case of a Gaussian
15.4
The case of a linear model
15.5
The really interesting case
15.6
Likelihood, above and beyond
16
Class 14: 10 10 2020 GLMs
16.1
What are GLMs
16.2
The link function
16.3
Most useful GLM Families
16.4
An example analysis
17
Class 15: 11 11 2020
18
Class 16: 17 11 2020
19
Final Words
References
Published with bookdown
Notes for Ecological Modelling
Chapter 17
Class 15: 11 11 2020