Probabilité

Probabilité

Dice of various shapes; Lecture 1 discusses rolls of a tetrahedral die. (Photograph courtesy of aranarth on Flickr.)

Probability is traditionally considered one of the most difficult areas of mathematics, since probabilistic arguments often come up with apparently paradoxical or counterintuitive results. Examples include the Monty Hall paradox and the birthday problem. Probability & Statistics introduces students to the basic concepts and logic of statistical reasoning and gives the students introductory-level practical ability to choose, generate, and properly interpret appropriate descriptive and inferential methods. In addition, the course helps students gain an appreciation for the diverse applications of statistics and its relevance to their lives. La probabilité est forte que ce soit ici, à nouveau, le cas. »C’est parce que je suis d’un avis contraire que j’ai eu envie de vous entretenir du sujet aujourd’hui.Les biais, d’abord.L’étude ne concerne pas des personnes prises au hasard, mais des volontaires.

Instructor(s)

Prof. John Tsitsiklis

Formules de base de la probabilité. The tools of probability theory, and of the related field of statistical inference, are the keys for being able to analyze and make sense of data. These tools underlie important advances in many fields, from the basic sciences to engineering and management. This resource is a companion site to 6.041SC Probabilistic Systems Analysis and Applied Probability. It covers the same content, using.

MIT Course Number

6.041 / 6.431

As Taught In

Fall 2010

Level

Undergraduate / Graduate

Probabilité

Some Description

Instructor(s)

Prof.

As Taught In

Spring 2002

Course Number

2.24

Level

Undergraduate/Graduate

Features

Lecture Notes, Student Work

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Course Description

Course Features

Course Description

Welcome to 6.041/6.431, a subject on the modeling and analysis of random phenomena and processes, including the basics of statistical inference. Nowadays, there is broad consensus that the ability to think probabilistically is a fundamental component of scientific literacy. For example:

  • The concept of statistical significance (to be touched upon at the end of this course) is considered by the Financial Times as one of 'The Ten Things Everyone Should Know About Science'.
  • A recent Scientific American article argues that statistical literacy is crucial in making health-related decisions.
  • Finally, an article in the New York Times identifies statistical data analysis as an upcoming profession, valuable everywhere, from Google and Netflix to the Office of Management and Budget.

The aim of this class is to introduce the relevant models, skills, and tools, by combining mathematics with conceptual understanding and intuition.

Probability 233 Definition

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Probability 233 Probability

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Probabilité

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