The Statistical Computing Series

The Statistical Computing Series is a monthly event for learning various aspects of modern statistical computing from practitioners in the Department of Biostatistics. We focus on topics related to the R language, Python, and related tools, but we include the broadest possible range of content related to effective statistical computation. The format varies, depending on the speaker and the topic, from lectures to demonstrations to hands-on workshops.

If you have a particular topic you would like to see covered, please send a request.

There have been several requests for coverage of various topics. Here is a short list, if you are interested in contributing but are seeking inspiration:

  • writing R functions with formula arguments
  • writing R functions with methods
  • using makefiles
  • other graphics packages (base graphics)
  • lme4/nlme
  • reshape (package not function)/plyr
  • R data structures
  • bootstrapping / random number generating
  • imputation (using various packages and functions)
  • bibtex
  • software for slide presentations

Time & Location

Fourth Friday of each month at 1:30 pm in the Biostatistics Conference Room (11105, 2525 West End Avenue).

Email Notification

We send out email notifications the week of a particular presentation. If you would like to be added to the list, please let us know.

Winter/Spring 2020 Schedule

The "Harrellverse"
24 January, 2020 Frank Harrell

Frank will describe the systems he has in place for managing communications, blog, operating system and R package updates, news feeds, file sharing, synchronizing computers, and other aspects of computer life.

Fall 2019 Schedule

API Construction for Scalable Delivery of Model Predictions using R and the Plumber package
23 August, 2019 Shawn Garbett

Intro to Bayesian Regression Modeling in R using rstanarm
27 September, 2019 Nathan James

Presentation slides

Creating and Distributing R Packages: A Case Study
25 October, 2019 Jeff Jetton

The thousands of available add-on packages are one of the reasons R has been so widely-adopted. This discussion will cover how (and why) R users might develop their own packages and, as an example, trace the journey of the “greenclust” package from its initial creation through to its recent submission to CRAN.

Spring 2019 Schedule

Tangram: Tools for Reproducible Tables
29 March, 2019 Shawn Garbett

Introduction to Docker
26 April, 2019 Nick Strayer


Fall 2018 Schedule

Getting Started with Bayesian Modeling in PyMC3

24 August, 2018 Chris Fonnesbeck


Improving organization and collaboration with Trello and integration with R

28 September, 2018 Molly Olson


Data Cleaning with dataMaid

26 October, 2018 Molly Olson and Omair Khan

Data screening is an important first step of any statistical analysis. dataMaid autogenerates a customizable data report with a thorough summary of the checks and the results that a human can use to identify possible errors. It provides an extendable suite of test for common potential errors in a dataset. Molly will provide an introductory tutorial for using dataMaid in your data analysis workflow. Omair will present an example of dataMaid's extendability.


Click to view previous presentations

Topic attachments
I Attachment Action Size Date Who Comment
bayes_reg_rstanarm.htmlhtml bayes_reg_rstanarm.html manage 2666.0 K 02 Oct 2019 - 09:08 JoshDeClercq Intro to Bayesian analysis in R
Topic revision: r157 - 08 Jan 2020, JoshDeClercq
 

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