Statistical Issues
Preface
How to read
Structure
Software
Acknowledgments
I Introduction
1
Introduction
II Statistics
2
Statistical Concepts
2.1
Measure Theory
2.1.1
Properties
2.1.2
Set algebra and countability
2.1.3
\(\sigma\)
-Algebras
III Inference
3
Statistical Inference
3.1
Classical Inference Techniques
3.2
Bayesian Inference Techniques
IV Modelling
4
Introduction {mod_intro}
4.1
Example one
4.2
Generalized additive models
4.3
GAM
4.4
GAM
4.5
Practice MGCV
4.5.1
Basics of gam model
4.5.2
Smoothing several variables
4.6
Survival Analysis
4.7
sub1
4.8
sub2
V Programming
5
Final Words
VI Mathematics
6
Linear Algebra
6.1
Linear Algebra Concepts
6.1.1
Linear Transformation
6.1.2
Change of Basis
6.1.3
Change of Basis for Linear Transformations
6.1.4
Eigenvalues and Eigenvectors
6.1.5
Cauchy–Schwartz inequality
7
here
8
Newton-Raphson and Gradient Descent
9
Here we go
References
Published with bookdown
Statistical Issues
Chapter 2
Statistical Concepts
Probability
Likelihood
Confidence Intervals
Statistical Methods
Classic Statistics
Bayesian statistics
Comparing classic and Bayesian statistics
Causality, Confounding