list 4 séquences
assignment Niveau : Introductif
label Mathématiques et Statistiques
chat_bubble_outline Langue : Anglais
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Les infos clés

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timer 12 heures de cours

En résumé

We will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R. We provide R programming examples in a way that will help make the connection between concepts and implementation. Problem sets requiring R programming will be used to test understanding and ability to implement basic data analyses. We will use visualization techniques to explore new data sets and determine the most appropriate approach. We will describe robust statistical techniques as alternatives when data do not fit assumptions required by the standard approaches. By using R scripts to analyze data, you will learn the basics of conducting reproducible research.

Given the diversity in educational background of our students we have divided the series into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts.

These courses make up 2 XSeries and are self-paced:

PH525.1x: Statistics and R for the Life Sciences

PH525.2x: Introduction to Linear Models and Matrix Algebra

PH525.3x: Statistical Inference and Modeling for High-throughput Experiments

PH525.4x: High-Dimensional Data Analysis

PH525.5x: Introduction to Bioconductor: annotation and analysis of genomes and genomic assays 

PH525.6x: High-performance computing for reproducible genomics

PH525.7x: Case studies in functional genomics


This class was supported in part by NIH grant R25GM114818.

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Le programme

  • Random variables
  • Distributions
  • Inference: p-values and confidence intervals
  • Exploratory Data Analysis
  • Non-parametric statistics
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Les intervenants

  • Rafael Irizarry
  • Michael Love
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Le concepteur

L’université Harvard (Harvard University), ou plus simplement Harvard, est une université privée américaine située à Cambridge, ville de l'agglomération de Boston, dans le Massachusetts. Fondée le 28 octobre 1636, c'est le plus ancien établissement d'enseignement supérieur des États-Unis.

Elle fait partie de l'Ivy League, regroupement informel des huit universités de la côte Est des États-Unis. Plus de 70 de ses étudiants ont reçu un prix Nobel. Le corps enseignant est constitué de 2 497 professeurs, pour 6 715 étudiants de premier cycle (undergraduate, en anglais) et 12 424 étudiants de cycle supérieur (graduate en anglais). Harvard attire des étudiants du monde entier (132 nationalités représentées en 2004).

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La plateforme

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EdX a été fondée par le Massachusetts Institute of Technology et par l'université Harvard en mai 2012. En 2014, environ 50 écoles, associations et organisations internationales offrent ou projettent d'offrir des cours sur EdX. En juillet 2014, elle avait plus de 2,5 millions d'utilisateurs suivant plus de 200 cours en ligne.

Les deux universités américaines qui financent la plateforme ont investi 60 millions USD dans son développement. La plateforme France Université Numérique utilise la technologie openedX, supportée par Google.

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