by Brian P. Ingalls

Chapters Used:

• Chapter 1: Introduction
• Chapter 2: Modeling of Chemical Reaction Networks
• Chapter 3: Biochemical Kinetics
• Chapter 4: Analysis of Dynamic Mathematical Models
• Chapter 5: Metabolic Networks
• Chapter 6: Signal Transduction Pathways
• Chapter 7: Gene Regulatory Networks

by Dan Graur and Wen-Hsiung Li

Chapters Used:

• Chapter 2: Dynamics of Genes in Populations

by Steven F. Railsback and Volker Grimm

Chapters Used:

• Chapter 1: Models, Agent-Based Models, and the Modeling Cycle
• Chapter 2: Getting Started with NetLogo
• Chapter 3: Describing and Formulating ABMs:  The ODD Protocol
• Chapter 4: Implementing a First Agent-Based Model
• Chapter 5: From Animations to Science
• Chapter 6: Testing Your Program
• Chapter 7: Introduction to Part II
• Chapter 8: Emergence

by David M Diez, Christopher D Barr, and Mine Çetinkaya-Rundel

Chapters Used:

• Chapter 1: Introduction to Data
• Chapter 4: Foundations of Inference
• Chapter 7: Introduction to Linear Regression
• Chapter 8: Multiple and Logistic Regression

by David R. Anderson

Chapters Used:

• Chapter 1:  Introduction: Science Hypotheses and Science Philosophy
• Chapter 2:  Data and Models
• Chapter 3:  Information Theory and Entropy
• Chapter 4:  Quantifying the Evidence About Science Hypotheses

Full Screen

Natural history museums around the world have been growing beyond display cases and dioramas for years, and many are digitizing their vast collections. These efforts create lasting records of the natural world that might otherwise be inaccessible, unless you know a friendly curator willing to take you behind the scenes. Below are several notable digitization efforts that you can explore, and even contribute to.

• I studied the relationship between predators, nest dispersion, and nest success.
• I built an agent-based model using data from nesting waterfowl, skunks, and foxes.
• Predation risk is diluted when nests are clustered and predation is incidental.
• When predators respond strongly to nest density, widely spaced nests survive better.
• Habitat management that imposes nest clustering could create ecological traps.

Forum post by Railsback in the Agent-Based and Individual-Based Modeling group.

by Sharon Machlis
edited by Johanna Ambrosio

Computerworld

R code examples for a number of common data analysis tasks

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This post examines the features of R Markdown using knitr in Rstudio 0.96. This combination of tools provides an exciting improvement in usability for reproducible analysis.

List of some really interesting mind-benders in probability.

Anyone want to try their hand at modeling this behavior?

Thanks, Amy Hurford!

By Nicolás E. Campione

Modified from: P. Dalgaard (2002). Introductory Statistics with R. Springer, New York. 

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Just getting started as an R user?  You can first try running R on QUBES Hub here, without installing anything.  Eventually, though you will want to install it on your own computer by downloading it here.  RStudio provides a friendlier interface for using R, and can be downloaded here.  Rstudio requires R to be installed, so start by downloading R.