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META TOPICPARENT name="Seminars"

The Statistical Computing Series

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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.
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Fall 2017 Schedule

Introduction to Jupyter Notebooks for Interactive and Reproducible Research!

29 September, 2017 Chris Fonnesbeck

Jupyter (formerly IPython) notebooks are a flexible and powerful tool for data science in both local and cloud-based environments. The notebooks allow data analyses to be integrated with markdown text, html, math, multimedia and other supporting materials and technologies to make scientific programming more literate and the generation of reports, web pages and even presentation slides seamless. While originally designed as a Python front-end, Jupyter works with R, Julia, Spark, and dozens of other languages via custom-built kernels. This presentation will introduce Jupyter notebooks and demonstrate how they can provide a powerful platform for reproducible quantitative research.

GitHub repository with notebook


Intermediate Version Control and Collaboration Workflows using Git and GitHub

27 October, 2017 Chris Fonnesbeck

Git has become a standard tool for version control of code for scientific computing and software development. Its effectiveness as a collaborative system is enhanced by commercial repository management services such as GitHub, BitBucket and GitLab, which provide remote repositories for working with teams on larger projects, as well as services for managing issues and code contributions from users. This tutorial will cover intermediate Git functionality required to use remote repositories effectively, including branching, cloning, merging and rebasing. I will also demonstrate best practices for participating in collaborative GitHub projects, such as creating issues and pull requests. This tutorial will assume participants are familiar with elementary Git usage.


Click to view previous presentations

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Spring 2017 Schedule

Use R to animate travel history!
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Plotting is not sufficient for data visualization in many cases, such as travel history data. People travel a lot, with family, with friends or alone. If you can animate your travel history, itís like reviving good memories. In this talk, I will briefly demonstrate how to plot data on Google Maps, draw great circles, and make animations using R!
  27 January, 2017 Minchun Zhou
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Plotting is not sufficient for data visualization in many cases, such as travel history data. People travel a lot, with family, with friends or alone. If you can animate your travel history, itís like reviving good memories. In this talk, I will briefly demonstrate how to plot data on Google Maps, draw great circles, and make animations using R!
  http://www.minchunzhou.com/travelhistory.html


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Probabilistic Modeling in TensorFlow Using the Edward Library
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Introduction to Variational Bayesian Methods

24 March, 2017 David Schlueter

In Bayesian analysis, the most common strategy for computing posterior quantities is through Markov Chain Monte Carlo (MCMC).†Despite recent advances in efficient sampling, MCMC methods still remain computationally intensive for more than a few thousand observations. A more scalable alternative to sampling is Variational Inference (VI), which re-frames the problem of computing the posterior distribution as a minimization of the Kullback-Leibler divergence between the true posterior and a member of some approximating family. In this talk, we provide a basic overview of the VI framework as well as practical examples of its implementation using the Automatic Differentiation Variational Inference (ADVI) engine in PyMC3.
 
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24 March, 2017 Chris Fonnesbeck
 


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Gaussian Processes Made Easy

28 April, 2017 Chris Fonnesbeck

A common applied statistics task involves building regression models to characterize non-linear relationships between variables. It is possible to fit such models by assuming a particular non-linear structure, such as a sinusoidal, exponential, or polynomial function, to describe a given response by one variable to another. Unless this relationship is obvious from the outset, however, it involves possibly extensive model selection procedures to ensure the most appropriate model is retained. Alternatively, a non-parametric approach can be adopted by defining a set of knots across the variable space and use a spline or kernel regression to describe arbitrary non-linear relationships. However, knot layout procedures are somewhat ad hoc and can also involve variable selection. A third alternative is to adopt a Bayesian non-parametric strategy, and directly model the unknown underlying function. For this, we can employ Gaussian process models. I will compare three packages for fitting GP models in Python that make building Bayesian non-parametric models easier than they have ever been.
 

Fall 2016 Schedule

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META TOPICPARENT name="Seminars"

The Statistical Computing Series

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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, 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.
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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.
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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.
Added:
>
>

Spring 2017 Schedule

Use R to animate travel history!

Plotting is not sufficient for data visualization in many cases, such as travel history data. People travel a lot, with family, with friends or alone. If you can animate your travel history, itís like reviving good memories. In this talk, I will briefly demonstrate how to plot data on Google Maps, draw great circles, and make animations using R!

27 January, 2017 Minchun Zhou

http://www.minchunzhou.com/travelhistory.html


Using the R package GMD to do collaborative statistical document construction

24 February, 2017 Nicholas Strayer

Lucy and I have recently made the R package GMD to solve the problem ďhow do you construct a statistical report/ homework while working simultaneously with collaborators?Ē. GMD is an alpha-level package that allows you to keep a local .Rmd file in sync with a remote google doc. Simply paste the share url of the google doc into the function and automatically R will pull the google doc, put it into an .Rmd on your local machine and render the results. This effectively letís you use google docs as your text editor, with all its benefits of history and multi-user editing while avoiding the hassle of continuously copying and pasting the text into R to check for syntax errors etc.


Probabilistic Modeling in TensorFlow Using the Edward Library

24 March, 2017 Chris Fonnesbeck


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Fall 2016 Schedule

A Not-so-gentle Introduction to Git

2 September, 2016 Dr. Christopher Fonnesbeck


Using RMarkdown to quickly make and maintain an attractive website

28 October, 2016 Mr. Nick Strayer and Ms. Lucy D'Agostino


A Tour of the TensorFlow Playground

2 December, 2016 Dr. Christopher Fonnesbeck


 

Fall 2015 Schedule

High-performance Computing with ACCRE
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Loop Efficiency in R
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META TOPICPARENT name="Seminars"

The Statistical Computing Series

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The Statistical Computing Series is a weekly 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, 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.
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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, 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.
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22 January 2016 Mr. Nick Strayer
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Slides


From Big to Lite Data with R/sqlite

26 February 2016 Mr. Cole Beck
 
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Creating Interactive Map Visualizations with Folium
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Getting Started with Jupyter Notebooks

22 April 2016 Dr. Chris Fonnesbeck

Static Jupyter notebook of presentation
 
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26 February 2016 Dr. Chris Fonnesbeck
 


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Data Management with Codex
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Pretty Data Visualization in R
 
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25 March 2016 Mr. David Biagi
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20 May 2016 Mr. Nick Strayer
 


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META TOPICPARENT name="Seminars"

The Statistical Computing Series

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High-performance Computing with ACCRE
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25 September 2015 Mr. Will French
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25 September 2015 Dr. Will French
 

ACCRE presentation slides
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Effective Text Editing with TextMate
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23 October, 2015 Dr. Christopher Fonnesbeck
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30 October, 2015 Dr. Christopher Fonnesbeck

Presentation summary
 


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A Primer on Regular Expressions

18 December, 2015 Mr. Jeremy Stephens


Spring 2016 Schedule

A Primer on Branching in Git

22 January 2016 Mr. Nick Strayer
 
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Power Text Editing using TextMate
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Creating Interactive Map Visualizations with Folium

26 February 2016 Dr. Chris Fonnesbeck


 
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9 January 2015 Dr. Chris Fonnesbeck
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Data Management with Codex
 
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TextMate editing tips
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25 March 2016 Mr. David Biagi
 


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Loop Efficiency in R

13 March 2015 Ms. Svetlana Eden
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META TOPICPARENT name="Seminars"

The Statistical Computing Series

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  • software for slide presentations

Time & Location

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Each Friday at 1:30 pm in the Biostatistics Conference Room (11105, 2525 West End Avenue).
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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.
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Fall 2014 Schedule

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Fall 2015 Schedule

High-performance Computing with ACCRE

25 September 2015 Mr. Will French

ACCRE presentation slides


Effective Text Editing with TextMate

23 October, 2015 Dr. Christopher Fonnesbeck


Computing on Larger-than-memory Datasets using Dask

20 November, 2015 Dr. Christopher Fonnesbeck


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Power Text Editing using TextMate

9 January 2015 Dr. Chris Fonnesbeck

TextMate editing tips


Loop Efficiency in R

13 March 2015 Ms. Svetlana Eden


Analyzing Geospatial Data using Python

10 April 2015 Dr. Chris Fonnesbeck


Presentations from Previous Years

 

Creating Interactive Visualizations with Bokeh
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Power Text Editing using TextMate

17 October, 2014 Dr. Chris Fonnesbeck


 
Using the REDCap API

7 November, 2014 Ms. JoAnn Alvarez and Dr. Chris Fonnesbeck
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Presentations from Previous Years

 
Introduction to String Matching and Modification in R Using Regular Expressions

17 January, 2014 Ms. Svetlana Eden
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The Statistical Computing Series

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Fall 2014 Schedule

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Enhanced Features of the Thunderbird Email Client
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Creating Interactive Visualizations with Bokeh

19 September, 2014 Dr. Chris Fonnesbeck
 
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12 September, 2014 Dr. Frank Harrell
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HTML Notebook
 


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Working with Tabular Data using cvskit
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Enhanced Features of the Thunderbird Email Client
 
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19 September, 2014 Dr. Chris Fonnesbeck
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26 September, 2014 Dr. Frank Harrell
 


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10 October, 2014 Mr. Minchun Zhou
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Slides


Power Text Editing using TextMate

17 October, 2014 Dr. Chris Fonnesbeck


Using the REDCap API

7 November, 2014 Ms. JoAnn Alvarez and Dr. Chris Fonnesbeck


Computing Clinic

Open forum for asking and answering statistical computing questions.

21 November, 2014
 

Click to view previous presentations

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META TOPICPARENT name="Seminars"

The Statistical Computing Series

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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.
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Spring 2014 Schedule

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Fall 2014 Schedule

Enhanced Features of the Thunderbird Email Client

12 September, 2014 Dr. Frank Harrell


Working with Tabular Data using cvskit

19 September, 2014 Dr. Chris Fonnesbeck


High Performance Computing in R Using the SNOW Package

10 October, 2014 Mr. Minchun Zhou


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Presentations from Previous Years

 

Introduction to String Matching and Modification in R Using Regular Expressions
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An Introduction to Data Wrangling with Pandas

7 February, 2014 Dr. Christopher Fonnesbeck


 
Writing Functions in R

14 February, 2014 Ms. Svetlana Eden


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Really Easy Slide Presentations with Slidify and RStudio
 
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Presentations from Previous Years

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28 February, 2014 Ms. Laurie Samuels

Looking for a simpler, cleaner alternative to Beamer? Slidify might be just the thing you're looking for. This short tutorial will cover just the basics; but even with just the basics, you can quickly make a nice-looking slide presentation with R code, graphs, tables, and even a formula or two.

Sample slide deck


 

Data manipulation with the apply functions in R, part I: apply, tapply, and lapply
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META TOPICPARENT name="Seminars"

The Statistical Computing Series

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  • writing R functions with formula arguments
  • writing R functions with methods
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  • using makefiles
 
  • other graphics packages (base graphics)
  • lme4/nlme
  • reshape (package not function)/plyr
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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.
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Fall 2013 Schedule

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Spring 2014 Schedule

Introduction to String Matching and Modification in R Using Regular Expressions

17 January, 2014 Ms. Svetlana Eden

presentation PDF

12 TextMate Tips for Effective Coding

24 January, 2014 Dr. Christopher Fonnesbeck

List of tips (Markdown format)


Efficiency Tips for a Basic R Loop

31 January, 2014 Ms. Svetlana Eden


Writing Functions in R

14 February, 2014 Ms. Svetlana Eden


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Presentations from Previous Years

 

Data manipulation with the apply functions in R, part I: apply, tapply, and lapply
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Using Plotly for Interactive and Collaborative Data Visualization
 
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Presentations from Previous Years

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Plotly is a collaborative data analysis and graphing platform. I will introduce its main features for generating high-quality, interactive scientific graphics using its APIs for Python and R.

6 December, 2013 Dr. Christopher Fonnesbeck


 

Evaluating and (automatically) typesetting symbolic calculus and linear algebra expressions using Sage and LaTeX
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META TOPICPARENT name="Seminars"

The Statistical Computing Series

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  • software for slide presentations

Time & Location

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Each Friday at 1:30 pm in the Biostatistics Conference Room (D-2221 MCN).
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Each Friday 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.
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Learn the basics of version control and code management!
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HTML5 slideshow
 

Increasing your leisure time as a biostatistician: Using the application programming interface (API) to automate exports in Redcap
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20 September, 2013 Mr. Nathan Mercaldo
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Statistical Computing Clinic

27 September, 2013
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Who is Stan?
 
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Bring your questions and issues to our scientific computing experts.
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25 October, 2013 Dr. Christopher Fonnesbeck
 


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1 November, 2013 Dr. Frank Harrell
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Length of the Beatles' Songs: An introduction to base graphics in R

8 November, 2013 Dr. Tatsuki Koyama


 
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Ten Simple Rules for Reproducible Computational Research
 
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A discussion of Sandve et al. 2013 paper

12 November, 2013 Dr. Christopher Fonnesbeck


 

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META TOPICPARENT name="Seminars"

The Statistical Computing Series

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Fall 2013 Schedule

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Data manipulation with the apply functions in R
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Data manipulation with the apply functions in R, part I: apply, tapply, and lapply
 

23 August, 2013 Ms. Laurie Samuels
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PDF of Sage notebook with demo code
 


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Bayesian modeling with PyMC 3
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A Gentle Introduction to Git and GitHub
 

30 August, 2013 Dr. Chris Fonnesbeck
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An overview of the newest version of PyMC.
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Learn the basics of version control and code management!
 


Increasing your leisure time as a biostatistician: Using the application programming interface (API) to automate exports in Redcap
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6 September, 2013 Ms. JoAnn Alvarez
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6 September, 2013 Ms. JoAnn Alvarez
 


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Data science and BiG Data Analytics
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Data science and BiG Data Analytics
 

13 September, 2013
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Recreating Minard: An introduction to base graphics in R

20 September, 2013 Mr. Nathan Mercaldo


 
Statistical Computing Clinic
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27 September, 2013
 

Bring your questions and issues to our scientific computing experts.
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META TOPICPARENT name="Seminars"

The Statistical Computing Series

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

Time & Location

Each Friday at 1:30 pm in the Biostatistics Conference Room (D-2221 MCN).
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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.
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Spring 2013 Schedule

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Fall 2013 Schedule

Data manipulation with the apply functions in R

23 August, 2013 Ms. Laurie Samuels


Bayesian modeling with PyMC 3

30 August, 2013 Dr. Chris Fonnesbeck

An overview of the newest version of PyMC.


Increasing your leisure time as a biostatistician: Using the application programming interface (API) to automate exports in Redcap

6 September, 2013 Ms. JoAnn Alvarez


Data science and BiG Data Analytics

13 September, 2013

Part I of a video training class by EMC.


Statistical Computing Clinic

20 September, 2013

Bring your questions and issues to our scientific computing experts.


Introduction to the SparseM package for ordinal models

1 November, 2013 Dr. Frank Harrell

Click to view previous presentations

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Presentations from Previous Years

 

Evaluating and (automatically) typesetting symbolic calculus and linear algebra expressions using Sage and LaTeX
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19 April, 2013 Mr. Scott Burns
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Resources: PDF HTML slides
 
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The Statistical Computing Series

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1 March, 2013 Ms. Jennifer Thompson
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Resources: Slides Example R code


Fitting Bayesian Survival Models in Python (Part 1)

15 March, 2013 Dr. Chris Fonnesbeck

Resources: iPython Notebook


Fitting Bayesian Survival Models in Python (Part 2)

22 March, 2013 Dr. Chris Fonnesbeck

Resources: iPython Notebook


Manipulating Structured Data with Pandas

12 April, 2013 Dr. Chris Fonnesbeck


Improving research using advanced REDCap interfaces

19 April, 2013 Mr. Scott Burns
 
Revision 70
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META TOPICPARENT name="Seminars"

The Statistical Computing Series

The Statistical Computing Series is a weekly 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, 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.
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If you have a particular topic you would like to see covered, please send a request to chris.fonnesbeck@vanderbilt.edu
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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:
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Time & Location

Each Friday at 1:30 pm in the Biostatistics Conference Room (D-2221 MCN).
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Fall 2012 Schedule

Handling date-times in R

30 August, 2012 Mr. Cole Beck Date-Time tutorial


Introductory Command Line Usage in Mac OS X

7 September, 2012 Dr. Chris Fonnesbeck


Mastering the TextMate Editor

14 September, 2012 Dr. Chris Fonnesbeck


Statistical Computing Clinic

12 October, 2012 General troubleshooting and Q&A for R and other tools.
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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.
 
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Spring 2013 Schedule

 
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Five Favorite Functions
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Evaluating and (automatically) typesetting symbolic calculus and linear algebra expressions using Sage and LaTeX
 
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19 October, 2012 Mr. Cole Beck Five Functions
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11 January, 2013 Ms. Laurie Samuels
 
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Resources: UsingSage
 
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How to Create Nomograms
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An Introduction to Graphics with D3
 
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2 November, 2012 Dr. Frank Harrell
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25 January, 2013 Dr. Chris Fonnesbeck
 


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An Introduction to Version Control Using Git
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Creating Heatmaps in R
 
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9 November, 2012 Dr. Chris Fonnesbeck
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15 February, 2013 Mr. Pengcheng Lu
 
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How to increase reproducibility by freezing R
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Resources: Report Sample R script
 
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16 November, 2012 Mr. Jeremy Stephens
 
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Spring 2013 Schedule

Evaluating and (automatically) typesetting symbolic calculus and linear algebra expressions using Sage and LaTeX
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Plotting with ggplot2
 
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1 March, 2013 Ms. Jennifer Thompson
 
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11 January, 2013 Ms. Laurie Samuels

Resources: UsingSage
 
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Fall 2012 Schedule

Handling date-times in R

30 August, 2012 Mr. Cole Beck Date-Time tutorial


Introductory Command Line Usage in Mac OS X

7 September, 2012 Dr. Chris Fonnesbeck


Mastering the TextMate Editor

14 September, 2012 Dr. Chris Fonnesbeck


Statistical Computing Clinic

12 October, 2012 General troubleshooting and Q&A for R and other tools.


Five Favorite Functions

19 October, 2012 Mr. Cole Beck Five Functions


How to Create Nomograms

2 November, 2012 Dr. Frank Harrell


An Introduction to Version Control Using Git

9 November, 2012 Dr. Chris Fonnesbeck


How to increase reproducibility by freezing R

16 November, 2012 Mr. Jeremy Stephens


  %ENDCHECK%

 
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