An Introduction to R Programming
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author: Jeffery Miecnikowski, Daniel Gaile, Rachael Hageman Blair
date: March 26, 2015
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Department of Biostatistics
School of Public Health and Health Professions, SUNY at Buffalo
Preliminary Instructions
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- The Workshop Webpage (and this file) can be found here:
[https://sphhp.buffalo.edu/biostatistics/news-events/workshops.html](https://sphhp.buffalo.edu/biostatistics/news-events/workshops.html)
- You can opt to use a virtual machine. To do so, follow the instructions at this link:
[http://www.cse.buffalo.edu/~chandola/workshops/cdsedays-2014/workshop-help.html](http://www.cse.buffalo.edu/~chandola/workshops/cdsedays-2014/workshop-help.html)
- Once you have started the virtual machine, open up a terminal and execute the following command:
- sudo apt-get install libcurl4-openssl-dev
- You can opt to install R and Rstudio on your laptop (recommended):
- [http://www.rstudio.com/products/rstudio/download/](http://www.rstudio.com/products/rstudio/download/)
- If help is needed, raise your hand and one of the student volunteers will assist.
Jeffery Miecnikowski, PhD
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- PhD Statistics 2006 Carnegie Mellon University
- Associate Dean for Faculty Affairs and Diversity, SPHHP
- Associate Professor, Department of Biostatistics
- Instructor for STA 511 and STA 521
- Co-authored several R packages
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Daniel Gaile, PhD
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- PhD Statistics 2003 Texas A\&M University
- Assistant Professor, Department of Biostatistics
- Director, Statistical Consulting Laboratory
- Instructor for STA 502 and STA 525
- Co-authored several R packages
- R User since ~1998
Rachael Hageman-Blair, PhD
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Overview of Talk
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This workshop is divided into three parts:
- Part I [Miecznikowski] : An overview and introduction to basic features of R.
- Part II [Gaile]: A very brisk overview of basic testing, visualization, dimension reduction and model building in R. Presented in the context of a STA525 (i.e.,'Bioinformatics') example.
- Part III [Hageman Blair]: An introduction to subset selection and model building in R. Presented in the context of STA545/546 (i.e., "Data Mining") examples.
.Rpres Presentations
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- These particular slides are admittedly plain. However, they showcase the .Rpres format available in R (and made all the more convenient in RStudio).
- Let's have a look at the IntroRmod0.Rpres file to see how these slides were generated.
- Open your own .Rpres file
- Explore the "Authoring R Presentations" help file.
- Bottomline: the R Markdown format provides for a convenient mechanism to quickly author presentation content.
Data Science and Statistics
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- Before we begin discussing R, we would like to address the attendees that are interested in pursuing educations related to "data science".
- The Department of Biostatistics offers courses for undergraduate, graduate and non-matriculated students.
- But why should a student that is interested in data science, consider taking courses in statistics?
Be a Unicorn!
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***
Or, an Awesome Nerd!
[Link to Source](http://www.datasciencecentral.com/profiles/blogs/data-science-the-end-of-statistics)
Opportunities to Learn Statistics and R
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[https://sphhp.buffalo.edu/biostatistics.html](https://sphhp.buffalo.edu/biostatistics.html)
Programs / Offerings
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[https://sphhp.buffalo.edu/biostatistics/education.html](https://sphhp.buffalo.edu/biostatistics/education.html)
- For Undergraduates: minor in Statistics
- For Graduate Students:
- Certificate Programs
- Advanced Graduate Certificate in Biostatistical Informatics
- Advanced Graduate Certificate in Applied Biostatistics
- MA and PhD in Biostatistics
- MA in Biostatics and Bioinformatics (moving from RPCI, June 2015)
- Note: can enroll as non-matriculated student
STA Courses Mentioned in This Talk
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- STA 502 [Gaile] Statistical Inference
- STA 511 [Miecznikowski] Mathematical Analysis for Biostatisticians
- STA 525 [Gaile] Statistics for Bioinformatics
- STA 545-546 [Hageman Blair] Data Mining I and II
Information regarding these courses can be found here:
[https://sphhp.buffalo.edu/biostatistics/education/biostatistics-ma/course-descriptions.html](https://sphhp.buffalo.edu/biostatistics/education/biostatistics-ma/course-descriptions.html)
Some Useful Links
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- [http://www.r-bloggers.com/how-to-learn-r-a-flow-chart/](http://www.r-bloggers.com/how-to-learn-r-a-flow-chart/)
- Nature: Statistics for Biologists: [http://www.nature.com/collections/qghhqm](http://www.nature.com/collections/qghhqm)
- Quick-R: [http://www.statmethods.net/](http://www.statmethods.net/)
Thanks!
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- Zhoulin He (not pictured), Biostatistics MA student. STA 545/STA 546