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Use Purdue OWL to annotate the paper Scale and Cross-Scale Dynamics: Governance and Information in a Multilevel World

Subject:
Applied Science
English Language Arts
Information Science
Material Type:
Activity/Lab
Homework/Assignment
Provider:
Science Education Resource Center (SERC) at Carleton College
Provider Set:
Teach the Earth
Author:
Richard David Gragg III
Date Added:
01/20/2023
Cover Crop Educational Modules
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Active learning modules to help students understand the role of cover crop species selection and design of mixed species cover crop plantings on multiple ecosystem services. Our current goal is to integrate lessons-learned from 8 years of research and extension activities into undergraduate education modules that can be widely distributed. Students completing these modules would be able to describe why cover crops are used, how different species of cover crop affect an array of ecosystem functions, how mixtures can be used to increase the multifunctionality of cover cropping systems, and factors that control mixture growth across sites. If the modules are delivered in the following order then these concepts build sequentially.

Subject:
Agriculture
Applied Science
Biology
Career and Technical Education
Ecology
Environmental Science
Life Science
Material Type:
Activity/Lab
Case Study
Diagram/Illustration
Interactive
Lesson
Lesson Plan
Module
Student Guide
Author:
Barbara Bariabar
Catalina Mejia
David Mortenson
Imtiaz Ahmad
Joseph Amsili
Mary Barbercheck
Michael Cahill
Richard Smith
Sarah Isbell
Tara Pisani Gareau
Jason Kaye
Date Added:
08/28/2020
Data Analysis and Visualization in R for Ecologists
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CC BY
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Data Carpentry lesson from Ecology curriculum to learn how to analyse and visualise ecological data in R. Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with ecology data in R. This is an introduction to R designed for participants with no programming experience. These lessons can be taught in a day (~ 6 hours). They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data frames, how to deal with factors, how to add/remove rows and columns, how to calculate summary statistics from a data frame, and a brief introduction to plotting. The last lesson demonstrates how to work with databases directly from R.

Subject:
Applied Science
Computer Science
Ecology
Information Science
Life Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Ankenbrand, Markus
Arindam Basu
Ashander, Jaime
Bahlai, Christie
Bailey, Alistair
Becker, Erin Alison
Bledsoe, Ellen
Boehm, Fred
Bolker, Ben
Bouquin, Daina
Burge, Olivia Rata
Burle, Marie-Helene
Carchedi, Nick
Chatzidimitriou, Kyriakos
Chiapello, Marco
Conrado, Ana Costa
Cortijo, Sandra
Cranston, Karen
Cuesta, Sergio Martínez
Culshaw-Maurer, Michael
Czapanskiy, Max
Daijiang Li
Dashnow, Harriet
Daskalova, Gergana
Deer, Lachlan
Direk, Kenan
Dunic, Jillian
Elahi, Robin
Fishman, Dmytro
Fouilloux, Anne
Fournier, Auriel
Gan, Emilia
Goswami, Shubhang
Guillou, Stéphane
Hancock, Stacey
Hardenberg, Achaz Von
Harrison, Paul
Hart, Ted
Herr, Joshua R.
Hertweck, Kate
Hodges, Toby
Hulshof, Catherine
Humburg, Peter
Jean, Martin
Johnson, Carolina
Johnson, Kayla
Johnston, Myfanwy
Jordan, Kari L
K. A. S. Mislan
Kaupp, Jake
Keane, Jonathan
Kerchner, Dan
Klinges, David
Koontz, Michael
Leinweber, Katrin
Lepore, Mauro Luciano
Li, Ye
Lijnzaad, Philip
Lotterhos, Katie
Mannheimer, Sara
Marwick, Ben
Michonneau, François
Millar, Justin
Moreno, Melissa
Najko Jahn
Obeng, Adam
Odom, Gabriel J.
Pauloo, Richard
Pawlik, Aleksandra Natalia
Pearse, Will
Peck, Kayla
Pederson, Steve
Peek, Ryan
Pletzer, Alex
Quinn, Danielle
Rajeg, Gede Primahadi Wijaya
Reiter, Taylor
Rodriguez-Sanchez, Francisco
Sandmann, Thomas
Seok, Brian
Sfn_brt
Shiklomanov, Alexey
Shivshankar Umashankar
Stachelek, Joseph
Strauss, Eli
Sumedh
Switzer, Callin
Tarkowski, Leszek
Tavares, Hugo
Teal, Tracy
Theobold, Allison
Tirok, Katrin
Tylén, Kristian
Vanichkina, Darya
Voter, Carolyn
Webster, Tara
Weisner, Michael
White, Ethan P
Wilson, Earle
Woo, Kara
Wright, April
Yanco, Scott
Ye, Hao
Date Added:
03/20/2017
Discover Psychology 2.0 - A Brief Introductory Text
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CC BY-NC-SA
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This textbook presents core concepts common to introductory courses. The 15 units cover the traditional areas of intro-to-psychology; ranging from biological aspects of psychology to psychological disorders to social psychology. This book can be modified: feel free to add or remove modules to better suit your specific needs.

This book includes a comprehensive instructor's manual, PowerPoint presentations, a test bank, reading anticipation guides, and adaptive student quizzes.

Subject:
Psychology
Social Science
Material Type:
Textbook
Provider:
Diener Education Fund
Provider Set:
Noba
Author:
Cara Laney
David M. Buss
David Watson
Edward Diener
Elizabeth F. Loftus
Emily Hooker
George Loewenstein
Henry L. Roediger III
Jeanne Tsai
Kathleen B. McDermott
Mark E. Bouton
Max H. Bazerman
Richard E. Lucas
Robert Siegler
Robert V. Levine
Ross Thompson
Sarah Pressman
Sudeep Bhatia
Susan T. Fiske
Yoshihisa Kashima
Date Added:
12/08/2016
Essentials of Communication
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CC BY-NC
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Short Description:
This is a collection of resources to complement ENGL128 Essentials of Communication, an introduction to the fundamentals of effective speaking and writing, exploring a variety of contexts in which language is used.

Word Count: 42931

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

Subject:
Business and Communication
Communication
Composition and Rhetoric
English Language Arts
Material Type:
Textbook
Provider:
University of Otago
Author:
David Mcmurrey
Elizabeth Browning
Jason S. Wrench
Kalani Pattison
Katherine S. Thweatt
Michael Cop
Narissra M. Punyanunt-Carter
Nicole Hagstrom-Schmidt
Patricia Williamson
Richard White
Date Added:
06/20/2023
Introduction to R for Geospatial Data
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CC BY
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The goal of this lesson is to provide an introduction to R for learners working with geospatial data. It is intended as a pre-requisite for the R for Raster and Vector Data lesson for learners who have no prior experience using R. This lesson can be taught in approximately 4 hours and covers the following topics: Working with R in the RStudio GUI Project management and file organization Importing data into R Introduction to R’s core data types and data structures Manipulation of data frames (tabular data) in R Introduction to visualization Writing data to a file The the R for Raster and Vector Data lesson provides a more in-depth introduction to visualization (focusing on geospatial data), and working with data structures unique to geospatial data.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Anne Fouilloux
Chris Prener
Claudia Engel
David Mawdsley
Erin Becker
François Michonneau
Ido Bar
Jeffrey Oliver
Juan Fung
Katrin Leinweber
Kevin Weitemier
Kok Ben Toh
Lachlan Deer
Marieke Frassl
Matt Clark
Miles McBain
Naupaka Zimmerman
Paula Andrea Martinez
Preethy Nair
Raniere Silva
Rayna Harris
Richard McCosh
Vicken Hillis
butterflyskip
Date Added:
08/07/2020
Is preregistration worthwhile?
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CC BY-NC-ND
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Proponents of preregistration argue that, among other benefits, it improves the diagnosticity of statistical tests. In the strong version of this argument, preregistration does this by solving statistical problems, such as family-wise error rates. In the weak version, it nudges people to think more deeply about their theories, methods, and analyses. We argue against both: the diagnosticity of statistical tests depend entirely on how well statistical models map onto underlying theories, and so improving statistical techniques does little to improve theories when the mapping is weak. There is also little reason to expect that preregistration will spontaneously help researchers to develop better theories (and, hence, better methods and analyses).

Subject:
Social Science
Material Type:
Primary Source
Author:
Chris Donkin
Danielle J. Navarro
David Kellen
Iris van Rooij
Richard Shiffrin
Trisha van Zandt
Aba Szollosi
Date Added:
11/13/2020
Library Carpentry: Introduction to Git
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CC BY
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Library Carpentry lesson: An introduction to Git. What We Will Try to Do Begin to understand and use Git/GitHub. You will not be an expert by the end of the class. You will probably not even feel very comfortable using Git. This is okay. We want to make a start but, as with any skill, using Git takes practice. Be Excellent to Each Other If you spot someone in the class who is struggling with something and you think you know how to help, please give them a hand. Try not to do the task for them: instead explain the steps they need to take and what these steps will achieve. Be Patient With The Instructor and Yourself This is a big group, with different levels of knowledge, different computer systems. This isn’t your instructor’s full-time job (though if someone wants to pay them to play with computers all day they’d probably accept). They will do their best to make this session useful. This is your session. If you feel we are going too fast, then please put up a pink sticky. We can decide as a group what to cover.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
222064h
Alex Mendes
Alexander Gary Zimmerman
Alexander Mendes
Amiya Maji
Amy Olex
Andrew Lonsdale
Annika Rockenberger
Begüm D. Topçuoğlu
Belinda Weaver
Benjamin Bolker
Bill McMillin
Brian Moore
Casey Youngflesh
Christoph Junghans
Christopher Erdmann
DSTraining
Dan Michael O. Heggø
David Jennings
Erin Alison Becker
Evan Williamson
Garrett Bachant
Grant Sayer
Ian Lee
Jake Lever
Jamene Brooks-Kieffer
James Baker
James E McClure
James O'Donnell
James Tocknell
Janoš Vidali
Jeffrey Oliver
Jeremy Teitelbaum
Jeyashree Krishnan
Joe Atzberger
Jonah Duckles
Jonathan Cooper
João Rodrigues
Katherine Koziar
Katrin Leinweber
Kunal Marwaha
Kurt Glaesemann
L.C. Karssen
Lauren Ko
Lex Nederbragt
Madicken Munk
Maneesha Sane
Marie-Helene Burle
Mark Woodbridge
Martino Sorbaro
Matt Critchlow
Matteo Ceschia
Matthew Bourque
Matthew Hartley
Maxim Belkin
Megan Potterbusch
Michael Torpey
Michael Zingale
Mingsheng Zhang
Nicola Soranzo
Nima Hejazi
Nora McGregor
Oscar Arbeláez
Peace Ossom Williamson
Raniere Silva
Rayna Harris
Rene Gassmoeller
Rich McCue
Richard Barnes
Ruud Steltenpool
Ryan Wick
Rémi Emonet
Samniqueka Halsey
Samuel Lelièvre
Sarah Stevens
Saskia Hiltemann
Schlauch, Tobias
Scott Bailey
Shari Laster
Simon Waldman
Stefan Siegert
Thea Atwood
Thomas Morrell
Tim Dennis
Tommy Keswick
Tracy Teal
Trevor Keller
TrevorLeeCline
Tyler Crawford Kelly
Tyler Reddy
Umihiko Hoshijima
Veronica Ikeshoji-Orlati
Wes Harrell
Will Usher
William Sacks
Wolmar Nyberg Åkerström
Yuri
abracarambar
ajtag
butterflyskip
cmjt
hdinkel
jonestoddcm
pllim
Date Added:
08/07/2020
Organizational Behavior
Unrestricted Use
CC BY
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This OpenStax resource aligns to introductory courses in Organizational Behavior. The text presents the theory, concepts, and applications with particular emphasis on the impact that individuals and groups can have on organizational performance and culture. An array of recurring features engages students in entrepreneurial thinking, managing change, using tools/technology, and responsible management; furthermore, the unique chapter on Social Media and Communication contextualizes the importance and implications of various platforms and communications methods.

Subject:
Business and Communication
Management
Material Type:
Textbook
Provider:
Rice University
Provider Set:
OpenStax College
Author:
David S. Bright
Donald G. Gardner
Eva Hartmann
J. Stewart Black
James S. O’Rourke
Jason Lambert
Jon L. Pierce
Joseph Weiss
Joy Leopold
Laura M. Leduc
Richard M. Steers
Siri Terjesen
Date Added:
06/05/2019
R for Reproducible Scientific Analysis
Unrestricted Use
CC BY
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0.0 stars

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
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CC BY
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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
Tools for Analysis: Design for Real Estate and Infrastructure Development
Conditional Remix & Share Permitted
CC BY-NC-SA
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This course is an introduction to the analytical tools that support design and decision-making in real estate and infrastructure development. There is a particular focus on identifying and valuing sources of flexibility using “real options”, Monte-Carlo simulation, and other techniques from the field of engineering systems. This course integrates economic and engineering perspectives, and is suitable for students with various backgrounds. It serves to provide useful preparation for thesis work in the area. The course applies the approach to the design and phasing of a mega infrastructure real estate project.
Note
This MIT OpenCourseWare site is based, in part, on materials on Design for Real Estate and Infrastructure Development from Professor de Neufville's and Professor Geltner's Web site.

Subject:
Applied Science
Business and Communication
Engineering
Mathematics
Social Science
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Geltner, David
de Neufville, Richard
Date Added:
02/01/2010
University Physics Volume 1
Unrestricted Use
CC BY
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0.0 stars

University Physics is a three-volume collection that meets the scope and sequence requirements for two- and three-semester calculus-based physics courses. Volume 1 covers mechanics, sound, oscillations, and waves. Volume 2 covers thermodynamics, electricity and magnetism, and Volume 3 covers optics and modern physics. This textbook emphasizes connections between between theory and application, making physics concepts interesting and accessible to students while maintaining the mathematical rigor inherent in the subject. Frequent, strong examples focus on how to approach a problem, how to work with the equations, and how to check and generalize the result.

Subject:
Physical Science
Physics
Material Type:
Textbook
Provider:
Rice University
Provider Set:
OpenStax College
Author:
Alice Kolakowska
Bill Moebs
Daniel Bowman
David Anderson
David Smith
Dedra Demaree
Edward S. Ginsberg
Gerald Friedman
Joseph Trout
Kenneth Podolak
Kevin Wheelock
Lee LaRue
Lev Gasparov
Mark Lattery
Patrick Motl
Richard Ludlow
Samuel J. Ling
Takashi Sato
Tao Pang
Date Added:
08/03/2016
Version Control with Git
Unrestricted Use
CC BY
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This lesson is part of the Software Carpentry workshops that teach how to use version control with Git. Wolfman and Dracula have been hired by Universal Missions (a space services spinoff from Euphoric State University) to investigate if it is possible to send their next planetary lander to Mars. They want to be able to work on the plans at the same time, but they have run into problems doing this in the past. If they take turns, each one will spend a lot of time waiting for the other to finish, but if they work on their own copies and email changes back and forth things will be lost, overwritten, or duplicated. A colleague suggests using version control to manage their work. Version control is better than mailing files back and forth: Nothing that is committed to version control is ever lost, unless you work really, really hard at it. Since all old versions of files are saved, it’s always possible to go back in time to see exactly who wrote what on a particular day, or what version of a program was used to generate a particular set of results. As we have this record of who made what changes when, we know who to ask if we have questions later on, and, if needed, revert to a previous version, much like the “undo” feature in an editor. When several people collaborate in the same project, it’s possible to accidentally overlook or overwrite someone’s changes. The version control system automatically notifies users whenever there’s a conflict between one person’s work and another’s. Teams are not the only ones to benefit from version control: lone researchers can benefit immensely. Keeping a record of what was changed, when, and why is extremely useful for all researchers if they ever need to come back to the project later on (e.g., a year later, when memory has faded). Version control is the lab notebook of the digital world: it’s what professionals use to keep track of what they’ve done and to collaborate with other people. Every large software development project relies on it, and most programmers use it for their small jobs as well. And it isn’t just for software: books, papers, small data sets, and anything that changes over time or needs to be shared can and should be stored in a version control system.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Alexander G. Zimmerman
Amiya Maji
Amy L Olex
Andrew Lonsdale
Annika Rockenberger
Begüm D. Topçuoğlu
Ben Bolker
Bill Sacks
Brian Moore
Casey Youngflesh
Charlotte Moragh Jones-Todd
Christoph Junghans
David Jennings
Erin Alison Becker
François Michonneau
Garrett Bachant
Grant Sayer
Holger Dinkel
Ian Lee
Jake Lever
James E McClure
James Tocknell
Janoš Vidali
Jeremy Teitelbaum
Jeyashree Krishnan
Jimmy O'Donnell
Joe Atzberger
Jonah Duckles
Jonathan Cooper
João Rodrigues
Katherine Koziar
Katrin Leinweber
Kunal Marwaha
Kurt Glaesemann
L.C. Karssen
Lauren Ko
Lex Nederbragt
Madicken Munk
Maneesha Sane
Marie-Helene Burle
Mark Woodbridge
Martino Sorbaro
Matt Critchlow
Matteo Ceschia
Matthew Bourque
Matthew Hartley
Maxim Belkin
Megan Potterbusch
Michael Torpey
Michael Zingale
Mingsheng Zhang
Nicola Soranzo
Nima Hejazi
Oscar Arbeláez
Peace Ossom Williamson
Pey Lian Lim
Raniere Silva
Rayna Michelle Harris
Rene Gassmoeller
Rich McCue
Richard Barnes
Ruud Steltenpool
Rémi Emonet
Samniqueka Halsey
Samuel Lelièvre
Sarah Stevens
Saskia Hiltemann
Schlauch, Tobias
Scott Bailey
Simon Waldman
Stefan Siegert
Thomas Morrell
Tommy Keswick
Traci P
Tracy Teal
Trevor Keller
TrevorLeeCline
Tyler Crawford Kelly
Tyler Reddy
Umihiko Hoshijima
Veronica Ikeshoji-Orlati
Wes Harrell
Will Usher
Wolmar Nyberg Åkerström
abracarambar
butterflyskip
jonestoddcm
Date Added:
03/20/2017
A call for transparent reporting to optimize the predictive value of preclinical research
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Deficiencies in methods reporting in animal experimentation lead to difficulties in reproducing experiments; the authors propose a set of reporting standards to improve scientific communication and study design. The US National Institute of Neurological Disorders and Stroke convened major stakeholders in June 2012 to discuss how to improve the methodological reporting of animal studies in grant applications and publications. The main workshop recommendation is that at a minimum studies should report on sample-size estimation, whether and how animals were randomized, whether investigators were blind to the treatment, and the handling of data. We recognize that achieving a meaningful improvement in the quality of reporting will require a concerted effort by investigators, reviewers, funding agencies and journal editors. Requiring better reporting of animal studies will raise awareness of the importance of rigorous study design to accelerate scientific progress.

Author:
Amelie K. Gubitz
Chris P. Austin
David W. Howells
Dimitri Krainc
Eileen W. Bradley
Ellis Unger
Howard E. Gendelman
Howard Fillit
John D. Porter
John Huguenard
John L. Goudreau
John M. McCall
Kalyani Narasimhan
Katrina Kelner
Khusru Asadullah
Linda J. Noble
Malcolm R. Macleod
Marc Fisher
Michael S. Levine
Oswald Steward
Richard T. Moxley III
Robert A. Gross
Robert B. Darnell
Robert Finkelstein
Robert J. Ferrante
Robert M. Golub
Robi Blumenstein
Ronald G. Crystal
Shai D. Silberberg
Sharon E. Hesterlee
Stanley E. Lazic
Steve Perrin
Story C. Landis
Susan G. Amara
Ursula Utz
Walter Koroshetz
Date Added:
08/08/2020