The R-Podcast Episode 11: Reproducible Analysis Part 1 (Introduction)

November 13, 2012
By

(This article was first published on The R-Podcast, and kindly contributed to R-bloggers)

Season 2 of the R-Podcast is up and running! This episode begins a multi-part series on reproducible analysis using R. In this episode I discuss the usage of Sweave and LaTeX for producing reproducible reports, an introduction to the capabilities of the knitr package (more episodes will be coming dedicated to this package), and my motivation for adapting reproducible analysis techniques and tools into my workflow. In our listener feedback segment I discuss a new means of providing feedback to the R-Podcast using our new sub-reddit page and introduce new segments highlighting interesting stories around the R community and useful packages. This promises to be an exciting season of the R-Podcast, and I hope you enjoy this episode!

The following resources are mentioned in this episode:

Episode 11 Time Stamps

00:00 The R-Podcast #011 Reproducible Analysis Part 1
00:40 Introduction
02:43 Reproducible Research: Introduction
08:18 Sweave overview
16:20 Knitr overview
20:20 The Duke University Research Saga
30:56 What version control can offer
38:34 Presenting results
42:18 Listener feedback
60:55 R community roundup
69:39 Package pick: plyr
72:04 Wrapping up: subscribe at www.r-podcast.org, [email protected], + 1-269-849-9780, Twitter @theRcast, Google Plus, links.r-podcast.org
77:21 End

To leave a comment for the author, please follow the link and comment on their blog: The R-Podcast.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Sponsors

Mango solutions



plotly webpage

dominolab webpage



Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training

datasociety

http://www.eoda.de





ODSC

ODSC

CRC R books series





Six Sigma Online Training









Contact us if you wish to help support R-bloggers, and place your banner here.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)