R for Sysadmins
LISA: Where systems engineering and operations professionals share real-world knowledge about designing, building, and maintaining the critical systems of our interconnected world.
The LISA conference has long served as the annual vendor-neutral meeting place for the wider system administration community. The LISA14 program recognized the overlap and differences between traditional and modern IT operations and engineering, and developed a highly-curated program around 5 key topics: Systems Engineering, Security, Culture, DevOps, and Monitoring/Metrics. The program included 22 half- and full-day training sessions; 10 workshops; and a conference program consisting of 50 invited talks, panels, refereed paper presentations, and mini-tutorials.
Grand Ballroom A
We provide a brief introduction to the R programming and statistics language, with a focus on exploratory data analysis for sysadmins. We assume little prior knowledge of statistics and no prior knowledge of the R language or programming environment. The course includes data input, basic manipulation, visualization and plotting, and basic analysis in R. The instructors will be available in the LISA Labs space after the tutorial for attendees that have additional questions or have brought their own data. R (http://www.r-project.org/) and RStudio (http://www.rstudio.com/), an IDE for R, should be installed prior to attending.
Sysadmins who would like an introduction to R as a tool for gaining additional insight into their wealth of data using R’s statistical and visualization capabilities. We assume little prior knowledge of R or statistics, but basic mathematical proficiency is recommended.
- Experience with basic methods and data types in R
- Experience with basic visualizations in R
- Basic understanding of data exploration, and analysis to identify patterns in R, such as correlations, regressions, and decision trees (as time allows)
- An introduction to R and the RStudio programming environment
- Basic instructions for loading, manipulating, and saving data
- Basic functions and algorithms for exploring data, and the types of analysis useful for sysadmins
- An introduction to descriptive statistics for single datasets, including: mean, median, mode, range, and distributions
- Basic visualizations in R, including histograms, scatterplots, and heatmaps (as time allows)






















