# Master Biomedical Engineering, M2 track Bioengineering and Innovation in Neuroscience

The whole statistics module is shared with the BioMat and BioMech tracks, as part of UE 3.2 "Research Methodology".
Parts I, II, III of the statistics module will be the subject of a 1h30 multiple-choice-questions test, followed by a 2h debriefing session. Part IV is the subject of a 3h+2h lecture, and of a R tutorial (4h computer session), which is relevant to UE 3.7-8 "Brain-computer interfaces : from modeling to engineering".

• Introduction (pdf)
• I. Probability space (pdf)
Sample space and events
The axioms of probability
Conditional probability, independence and Bayes theorem
Application to the evaluation of a diagnostic test
• II. Random variables (pdf)
Definitions, descriptive statistics
Discrete probability distributions
Continuous probability distributions
• III. Point and interval estimation (pdf)
Point estimation
Interval estimation
Examples drawn from publications
• IV. Statistical hypothesis testing (pdf)
Decision and probabilities of error
Comparing two samples
P-value and type I error risk
Chi-square tests
One-way analysis of variance
Summary of the tests
Corrections for multiple testing

STATISTICAL TABLES

• Standard normal (jpg)
• Student (pdf)
• Pearson (pdf)
• Fisher (pdf)
• Poisson (pdf)

TUTORIAL WITH R

THE R SOTFWARE FOR STATISTICAL COMPUTING

RECOMMENDED BOOKS

• In French, rather for engineers : G. Saporta (2011), Probabilités, analyse des données et Statistique, Editions TECHNIP.
• In English, rather for engineers : A. Hayter (2013), Probability and statistics for engineers and scientists, Brooks/Cole.
• Also in English, less technical with many exercises : R. B. Schinazi (2012), Probability with statistical applications, Birkhaüser.
In case you may want to have look at these books before purchasing them, I have copies at my lab.

RECOMMENDED STATISTICS SITE

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