1. Parallel and Cluster Computing with R

    2016-09-27

    Taking better advantage of hardware to speed up our software

  2. Floating Point Arithmetic for Data Analysts

    2016-07-28

    How our computers store and operate on real numbers

  3. Data Intake: Defining, Cleaning and Merging

    2016-04-09

    Basic data intake notes for DataFest 2016

  4. Automated R Clusters on AWS

    2016-02-17

    Minimum viable clusters presentation for StatProgDC

  5. Pseudo-Random Number Generators

    2016-02-05

    Pseudo-random number generators for statistical analysis

  6. Amazon Web Services for Data Analysis

    2015-11-12

    AWS products relevant to data analysts

  7. Gitting Started: Git and GitLab

    2015-10-05

    First steps with Git and GitLab

  8. Mapping in R

    2015-07-31

    Principles of map graphics, recommended functions and packages

  9. Robust Regression: Theory and Implementation in R

    2015-03-13

    A primer on robust regression methods