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Feel the Stress
Read the Fine Print
Educational Use
Rating
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Working individually or in groups, students explore the concept of stress (compression) through physical experience and math. They discover why it hurts more to poke themselves with mechanical pencil lead than with an eraser. Then they prove why this is so by using the basic equation for stress and applying the concepts to real engineering problems.

Subject:
Applied Science
Engineering
Geometry
Life Science
Mathematics
Physical Science
Physics
Material Type:
Activity/Lab
Provider:
TeachEngineering
Provider Set:
TeachEngineering
Author:
Jeffrey Mitchell
Date Added:
09/18/2014
R for Reproducible Scientific Analysis
Unrestricted Use
CC BY
Rating
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