About this lecture

Hello and Welcome to this introductory Lecture in Probability!

These Course Notes are a complement to the Lecture Probability I.

Contents

The Lecture is divided in the following Chapters, and each Chapter contains several themes.

Number Name Themes Status
1 Introduction Intro, Mathematics reminder and Combinatorics. ☑️
2 Elements of Set Theory For Probability Random variables, Trees, Venn diagram, Conditional probability, Independence & Bayes’ theorem. ☑️
3 Axiomatic Foundations of Probability Probability Axioms, Illustrations of use ☑️
4 Discrete random variables Definitions, Expected value and variance, Binomial, Poisson, Negative binomial and Hypergeometric 🔧
5 Continuous random variables Definitions, Expected value and variance, Cumulative distribution function (cdf) and Probability density function (pdf), Some important examples: Uniform, Exponential, Gamma, Normal, logNormal, Student’s t, Relationships 🔧
6 Limit Theorems Weak Law of Large Numbers (WLLN) and Central Limit Theorem (CLT) 📝
7 Bivariate Discrete Random Variables 📝
8 Elements of Simulation Numerical methods for the simulation of random variable with a given CDF. 📝
  • ☑️ = Ready (almost surely with typos).
  • 🔧 = Fine-tuning.
  • 📝 = Writing.

Practical information

Who we are

Daniel FLORES AGREDA
Daniel FLORES AGREDA
Data Science Course Developer and Instructor
Daniel.Flores@unige.ch
Edoardo VIGNOTTO
Edoardo VIGNOTTO
Teaching and Research Assistant
Edoardo.Vignotto@unige.ch
Davide LA VECCHIA
Davide LA VECCHIA
Associate Professor at Geneva School of Economics and Management
Davide.Lavecchia@unige.ch
Manon FELIX
Manon FELIX
Teaching and Research Assistant, PhD. student at Geneva School of Economics and Management
Manon.Felix@unige.ch
Alice Scattolin
Alice Scattolin
Teaching and Research Assistant, PhD. student at Geneva School of Economics and Management
Alice.Scattolin@unige.ch

Instructors

  • Davide La Vecchia, Associate Professor at Geneva School of Economics and Management
  • M. Manon Felix, Teaching and Research Assistant, PhD. student at Geneva School of Economics and Management
  • M. Alice Scattolin, Teaching and Research Assistant, PhD. student at Geneva School of Economics and Management

Lectures

The Lectures will take place in the room MR280 on Thursday from 12h15 to 14h00. For those students who cannot attend the lectures, a recording will be available on Mediaserver.

Exercises

Seminars will take place on Thursday from 16h15 to 18h00 in the room MS130. The seminars are not recorded.

Tutorials

Every two week (starting from the third one), tutorials will take place on Wednesday from 16h15 to 18h00 in the room MS160. The tutorials are not recorded.

Tools

You have access to a new forum on SpeakUp to submit your potential questions.

Reference

Aside from these Course Notes, you can check:

  • A first course in probability, S. Ross (any edition), Ed: Pearson New International Edition, cited as Ross (2014).

We will not be following the content of this book beat-by-beat, but it is available for reference and/or in case you want a different explanation or go deeper in the context of the Course.

References

Ross, Sheldon. 2014. A First Course in Probability. Pearson.