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Participant: Amit Gal, The Open U. of Israel
Participant: Avner Kantor, U. of Haifa
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| R is an open source environment for data analysis that has recently become popular in both industry and academia. Besides R's superior capabilities in performing advanced statistical analyses and fitting complex models, R also provides an end-to-end support for the whole research process under the same environment. This support includes tools whose purpose is to improve and facilitate research productivity by substantially reducing time required for data preparation for analysis (e.g. recoding variables, merging data from various sources, data aggregation, etc.) and report production (e.g. creating and exporting tables and graphs), preventing errors, and defining analysis procedures that are reproducible and flexible so that they can be easily applied or re-applied for different data in different frameworks. The purpose of this PDW is to introduce participants to these tools by demonstrating how they apply to several real research tasks. This will be accomplished through an interactive session in which participants can follow an initial script, and be able to try adapting it to their needs under the guidance of the organizers. The material covered will include advanced R packages such as dplyr, knitr, and more, presented after a short introduction to R, so that participants with no prior R experience can still benefit from the session. As the organizers are active in R package development, the end of the session will be dedicated to an open Q&A discussion about research productivity issues researchers encounter, and how they could be addressed in future R packages. |
| We will learn to manipulate and prepare data for analysis more easily, including merging, computing and recoding variables, aggregating data etc., and we'll also look at creating tables and graphs. The PDW will start with a short R introduction, will cover the dplyr package for data manipulation in detail, then cover the xtable, knitr and stargazer packages to cover reporting capabilities. The basic principles of the R markdown for reproducible research will be introduced as well. This is an hands-on workshop. Please come with a Laptop with R installed. No previous R experience required. |
| Search Terms: R | data preparation | reproducible research |
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