Morning session - Data analysis using R - Research - Institut Pasteur

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Assistant Professor
Associate Professor
Clinical Research Assistant
Clinical Research Nurse
Clinician Researcher
Department Manager
Dual-education Student
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Honorary Professor
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Master Student
Non-permanent Researcher
Nursing Staff
Permanent Researcher
Pharmacist
PhD Student
Physician
Post-doc
Prize
Project Manager
Research Associate
Research Engineer
Retired scientist
Technician
Undergraduate Student
Veterinary
Visiting Scientist

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Deputy Director of Center
Deputy Director of Department
Deputy Director of National Reference Center
Deputy Head of Facility
Director of Center
Director of Department
Director of Institute
Director of National Reference Center
Group Leader
Head of Facility
Head of Operations
Head of Structure
Honorary President of the Departement
Labex Coordinator

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Morning session – Introduction to NGS data analysis

Introduction to Data Analysis

Scientific Fields

Diseases

Organisms

Applications

Technique

Starting Date

08

Mar 2016

Ending Date

12

Apr 2016

Time

09:00:00

28 Rue du Docteur Roux, Paris, France

Address

Building: Lwoff

Location

2016-03-08 09:00:00 2016-04-12 12:00:00 Europe/Paris Morning session – Data analysis using R This course is an introduction to data analysis. It is better to have a minimal knowledge of R. If not, an introductory tutorial is available on the course’s web page and the basics of […] 28 Rue du Docteur Roux, Paris, France Marie-Agnès Dillies marie-agnes.dillies@pasteur.fr

This course is an introduction to data analysis. It is better to have a minimal knowledge of R. If not, an introductory tutorial is available on the course’s web page and the basics of R will be recalled during practice. For people who have never used R, it may be useful to have basic programming skills, regardless of the language. The course is for people who want to learn or re-learn how to use the statistics wisely for their own projects. The objective is to present and explain the main concepts of statistics useful for describing a dataset, exploring its properties in order to draw robust conclusions, making good use of the most common methods (hypothesis tests, PCA , …) and knowing how to read, interpret (and possibly approach critically) the results presented in the publications. We will use mathematical formalism as little as possible, but insist on the properties of the methods, their prerequisites, the interpretation of the results. We will discuss the notions of exploratory analysis, Principal Component Analysis (PCA), clustering, estimation, sampling, regression, hypothesis testing, experimental design.
Lectures will take place every tuesday morning from 9 to noon.

Location

Location: 28 Rue du Docteur Roux, Paris, France

Published on: 19 Jul 2018

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