Lecture notes for G5703

These informal notes are a complement to the slides and materials covered during the year 2018-2019 for the course ``Statistical Inference and Modeling''. They have not been subject to the scrutiny of formal publications. No originality is claimed for their contents. The notes are largely but not solely inspired by references listed below.

1. Introduction
2. Parametric estimation
3. Confidence intervals and hypothesis testing
4. Exponential family and sufficiency
5. Straight line regression
6. Survival data
7. Missing data
8. Multivariate normal data
9. Discrete Markov chains
10. Time series
11. Linear regression model
12. Generalized linear models
13. Nonparametric regression
14. Generalized additive models
15. Bayesian statistics

Main references

• Statistical Models, A. Davison (2003)
• Generalized Additive Models, 2nd edition, by S. Wood (2017)
• Mathematical Statistics, by K. Knight (1999)

Other references

• Slides of the course Fundamentals of Statistics taught by V.E. Brunel at MIT.
• Lecture notes for the course Principles of Statistics taught by Q. Berthet at the University of Cambridge.
• Lecture notes on Nonparametric Smoothing by A. Bowman and L. Evers at the University of Glasgow.