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R for Reproducible Scientific Analysis
Unrestricted Use
CC BY
Rating
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This lesson in part of Software Carpentry workshop and teach novice programmers to write modular code and best practices for using R for data analysis. an introduction to R for non-programmers using gapminder data The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation. Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis. The lesson contains more material than can be taught in a day. The instructor notes page has some suggested lesson plans suitable for a one or half day workshop. A variety of third party packages are used throughout this workshop. These are not necessarily the best, nor are they comprehensive, but they are packages we find useful, and have been chosen primarily for their usability.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Adam H. Sparks
Ahsan Ali Khoja
Amy Lee
Ana Costa Conrado
Andrew Boughton
Andrew Lonsdale
Andrew MacDonald
Andris Jankevics
Andy Teucher
Antonio Berlanga-Taylor
Ashwin Srinath
Ben Bolker
Bill Mills
Bret Beheim
Clare Sloggett
Daniel
Dave Bridges
David J. Harris
David Mawdsley
Dean Attali
Diego Rabatone Oliveira
Drew Tyre
Elise Morrison
Erin Alison Becker
Fernando Mayer
François Michonneau
Giulio Valentino Dalla Riva
Gordon McDonald
Greg Wilson
Harriet Dashnow
Ido Bar
Jaime Ashander
James Balamuta
James Mickley
Jamie McDevitt-Irwin
Jeffrey Arnold
Jeffrey Oliver
John Blischak
Jonah Duckles
Josh Quan
Julia Piaskowski
Kara Woo
Kate Hertweck
Katherine Koziar
Katrin Leinweber
Kellie Ottoboni
Kevin Weitemier
Kiana Ashley West
Kieran Samuk
Kunal Marwaha
Kyriakos Chatzidimitriou
Lachlan Deer
Lex Nederbragt
Liz Ing-Simmons
Lucy Chang
Luke W Johnston
Luke Zappia
Marc Sze
Marie-Helene Burle
Marieke Frassl
Mark Dunning
Martin John Hadley
Mary Donovan
Matt Clark
Melissa Kardish
Mike Jackson
Murray Cadzow
Narayanan Raghupathy
Naupaka Zimmerman
Nelly Sélem
Nicholas Lesniak
Nicholas Potter
Nima Hejazi
Nora Mitchell
Olivia Rata Burge
Paula Andrea Martinez
Pete Bachant
Phil Bouchet
Philipp Boersch-Supan
Piotr Banaszkiewicz
Raniere Silva
Rayna Michelle Harris
Remi Daigle
Research Bazaar
Richard Barnes
Robert Bagchi
Rémi Emonet
Sam Penrose
Sandra Brosda
Sarah Munro
Sasha Lavrentovich
Scott Allen Funkhouser
Scott Ritchie
Sebastien Renaut
Thea Van Rossum
Timothy Eoin Moore
Timothy Rice
Tobin Magle
Trevor Bekolay
Tyler Crawford Kelly
Vicken Hillis
Yuka Takemon
bippuspm
butterflyskip
waiteb5
Date Added:
03/20/2017
R para Análisis Científicos Reproducibles
Unrestricted Use
CC BY
Rating
0.0 stars

Una introducción a R utilizando los datos de Gapminder. El objetivo de esta lección es enseñar a las programadoras principiantes a escribir códigos modulares y adoptar buenas prácticas en el uso de R para el análisis de datos. R nos provee un conjunto de paquetes desarrollados por terceros que se usan comúnmente en diversas disciplinas científicas para el análisis estadístico. Encontramos que muchos científicos que asisten a los talleres de Software Carpentry utilizan R y quieren aprender más. Nuestros materiales son relevantes ya que proporcionan a los asistentes una base sólida en los fundamentos de R y enseñan las mejores prácticas del cómputo científico: desglose del análisis en módulos, automatización tareas y encapsulamiento. Ten en cuenta que este taller se enfoca en los fundamentos del lenguaje de programación R y no en el análisis estadístico. A lo largo de este taller se utilizan una variedad de paquetes desarrolados por terceros, los cuales no son necesariamente los mejores ni se encuentran explicadas todas sus funcionalidades, pero son paquetes que consideramos útiles y han sido elegidos principalmente por su facilidad de uso.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
0xgc
A. s
Alejandra Gonzalez-Beltran
Ana Beatriz Villaseñor Altamirano
Antonio
AntonioJBT
Belinda Weaver
Claudia Engel
Cynthia Monastirsky
Daniel Beiter
David Mawdsley
David Pérez-Suárez
Erin Becker
EuniceML
François Michonneau
Gordon McDonald
Guillermina Actis
Guillermo Movia
Hely Salgado
Ido Bar
Ivan Ogasawara
Ivonne Lujano
James J Balamuta
Jamie McDevitt-Irwin
Jeff Oliver
Jonah Duckles
Juan M. Barrios
Katrin Leinweber
Kevin Alquicira
Kevin Martínez-Folgar
Laura Angelone
Laura-Gomez
Leticia Vega
Marcela Alfaro Córdoba
Marceline Abadeer
Maria Florencia D'Andrea
Marie-Helene Burle
Marieke Frassl
Matias Andina
Murray Cadzow
Narayanan Raghupathy
Naupaka Zimmerman
Paola Prieto
Paula Andrea Martinez
Raniere Silva
Rayna M Harris
Richard Barnes
Richard McCosh
Romualdo Zayas-Lagunas
Sandra Brosda
Sasha Lavrentovich
Shirley Alquicira Hernandez
Silvana Pereyra
Tobin Magle
Veronica Jimenez
juli arancio
raynamharris
saynomoregrl
Date Added:
08/07/2020
The Unix Shell
Unrestricted Use
CC BY
Rating
0.0 stars

Software Carpentry lesson on how to use the shell to navigate the filesystem and write simple loops and scripts. The Unix shell has been around longer than most of its users have been alive. It has survived so long because it’s a power tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren’t typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources (including “high-performance computing” supercomputers). These lessons will start you on a path towards using these resources effectively.

Subject:
Applied Science
Computer Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Adam Huffman
Adam James Orr
Adam Richie-Halford
AidaMirsalehi
Alex Kassil
Alex Mac
Alexander Konovalov
Alexander Morley
Alix Keener
Amy Brown
Andrea Bedini
Andrew Boughton
Andrew Reid
Andrew T. T. McRae
Andrew Walker
Ariel Rokem
Armin Sobhani
Ashwin Srinath
Bagus Tris Atmaja
Bartosz Telenczuk
Ben Bolker
Benjamin Gabriel
Bertie Seyffert
Bill Mills
Brian Ballsun-Stanton
BrianBill
Camille Marini
Chris Mentzel
Christina Koch
Colin Morris
Colin Sauze
Damien Irving
Dan Jones
Dana Brunson
Daniel Baird
Daniel McCloy
Daniel Standage
Danielle M. Nielsen
Dave Bridges
David Eyers
David McKain
David Vollmer
Dean Attali
Devinsuit
Dmytro Lituiev
Donny Winston
Doug Latornell
Dustin Lang
Elena Denisenko
Emily Dolson
Emily Jane McTavish
Eric Jankowski
Erin Alison Becker
Ethan P White
Evgenij Belikov
Farah Shamma
Fatma Deniz
Filipe Fernandes
Francis Gacenga
François Michonneau
Gabriel A. Devenyi
Gerard Capes
Giuseppe Profiti
Greg Wilson
Halle Burns
Hannah Burkhardt
Harriet Alexander
Hugues Fontenelle
Ian van der Linde
Inigo Aldazabal Mensa
Jackie Milhans
Jake Cowper Szamosi
James Guelfi
Jan T. Kim
Jarek Bryk
Jarno Rantaharju
Jason Macklin
Jay van Schyndel
Jens vdL
John Blischak
John Pellman
John Simpson
Jonah Duckles
Jonny Williams
Joshua Madin
Kai Blin
Kathy Chung
Katrin Leinweber
Kevin M. Buckley
Kirill Palamartchouk
Klemens Noga
Kristopher Keipert
Kunal Marwaha
Laurence
Lee Zamparo
Lex Nederbragt
M Carlise
Mahdi Sadjadi
Marc Rajeev Gouw
Marcel Stimberg
Maria Doyle
Marie-Helene Burle
Marisa Lim
Mark Mandel
Martha Robinson
Martin Feller
Matthew Gidden
Matthew Peterson
Megan Fritz
Michael Zingale
Mike Henry
Mike Jackson
Morgan Oneka
Murray Hoggett
Nicola Soranzo
Nicolas Barral
Noah D Brenowitz
Noam Ross
Norman Gray
Orion Buske
Owen Kaluza
Patrick McCann
Paul Gardner
Pauline Barmby
Peter R. Hoyt
Peter Steinbach
Philip Lijnzaad
Phillip Doehle
Piotr Banaszkiewicz
Rafi Ullah
Raniere Silva
Robert A Beagrie
Ruud Steltenpool
Ry4an Brase
Rémi Emonet
Sarah Mount
Sarah Simpkin
Scott Ritchie
Stephan Schmeing
Stephen Jones
Stephen Turner
Steve Leak
Stéphane Guillou
Susan Miller
Thomas Mellan
Tim Keighley
Tobin Magle
Tom Dowrick
Trevor Bekolay
Varda F. Hagh
Victor Koppejan
Vikram Chhatre
Yee Mey
csqrs
earkpr
ekaterinailin
nther
reshama shaikh
s-boardman
sjnair
Date Added:
03/20/2017