This short talk provides some brief history and perspective about networks, RCNs, and the RCN-UBE program. Notes from a report from the 2005 RCN awardees meeting (when the RCN program was similar in size to the current RCN-UBE) were shared in which the participants shared best practices and identified some elements of successful RCNs. Some information about the past and current RCN-UBE portfolio were shared and some representative past awards highlighted. The talk ends with a list of goals that calls for a vision for the future, recommendations for best practices (targeting all stakeholders), continuing networking and communication, and a report summarizing our conversations and ideas.

Welcome to Data Is Ugly, a sub all about butchered visualizations, misleading charts and unlabelled axes. If you've found a particularly useless/ugly/unreadable chart or infographic, and struggled to find someone who will listen to your complaints, then rejoice, for you are home!

Website

A place for visual representations of data: Graphs, charts, maps, etc.

DataIsBeautiful is for visualizations that effectively convey information. Aesthetics are an important part of information visualization, but pretty pictures are not the aim of this subreddit.

Website

From Wikipedia:

Plotly offers six main products:

• Plot.ly has a graphical user interface for importing and analyzing data into a grid and using stats tools. Graphs can be embedded or downloaded. Mainly used to make creating graphs faster and more efficient.
• API libraries for Python, R, MATLAB, Node.js, Julia, and Arduino and a REST API. Plotly can also be used to style interactive graphs with IPython.
• Figure Converters which convert matplotlib, ggplot2, and IGOR Pro graphs into interactive, online graphs.
• Plotly Apps for Google Chrome.
• Plotly.js is an open source JavaScript library for creating graphs and dashboards.
• Plotly Enterprise an on-premises installation of Plotly.

Website

CUREnet is a network of people and programs that are creating course-based undergraduate research experiences (CUREs) in biology.

Short read with some concrete suggestions for integrating teaching and research.

Datasets  R Code  R Pubs

Sampling from a normally distributed population

Confidence intervals for the mean

Datasets  R Code  R Pubs

Last year, I presented an informal course on the basics of R Graphics University of Turku. In this blog post, I am providing some of the slides and the full code from that practical, which shows how to build different plot types using the basic (i.e. pre-installed) graphics in R

Website Supplementary Files

These notes are an introduction to using the statistical software package R for an introductory statistics course. They are meant to accompany an introductory statistics book such as Kitchens “Exploring Statistics”. The goals are not to show all the features of R, or to replace a standard textbook, but rather to be used with a textbook to illustrate the features of R that can be learned in a one-semester, introductory statistics course.

Download

READ ME FIRST:  This collection provides additional resources to support classes teaching from The Analysis of Biological Data by Michael Whitlock and Dolph Schluter, broken down by chapter.  Each chapter post has at least three buttons:  Datasets, which links to the datasets for that chapter; R Code, which links to the R code for that chapter; and R Pubs, which links to a different version of the R code page that contains additional code output and results.

Website

Datasets  R Code  R Pubs

Summary table of plots (by Kyla Jackson)

A free online tutorial for learning basic R commands.  It runs through your browser and does not require you to install R.

R code examples for a number of common data analysis tasks

by Sharon Machlis
edited by Johanna Ambrosio

Computerworld