This file contains a global overview of all of the resources for RStudio in Professor Wilson’s statistics courses, along with the role they play, and the rationale for using this software. All of these resources are hyperlinked, and they are also found on the RTutorials page, https://sites.google.com/a/biola.edu/rtutorials/.
1. Installation: Installing R and RStudio contains everything you need to download and install R & RStudio on your computer (free). For the RStudio Cloud option, go to https://rstudio.cloud.
2. Data: Download the appropriate file for your course (General: States95 & UCR; Math 318 Biostats: WS_Ch1-17.RData. The video tutorial for loading the data is: Load_Data)
3. Learning the software
a. See "2. RStudio Introduction Videos, Data, and Scripts" on the R Materials page. This provides the script files, data, and optional videos to walk you through everything you need to get started with RStudio.
b. Tutorials: For assignments in class, see class specifics. A good online text tutorial is www.r-tutor.com.
c. R_Scripts_Index.pdf: My handout with the primary base R commands with basic syntax.
d. Base R Cheatsheet: Reference sheet with primary base R commands
e. Mosaic Cheatsheet: Reference sheet with mosaic package commands
4. Additional Resources
a. Script files will be posted on Canvas as the semester proceeds (impromptu and prepared files)
b. Video Tutorials: assorted R topics on R Materials page
c. R Manual: Manual for students written (optional) on R Materials page
d. Note: R Help files are accessed in the 'Help' tab in the lower right window, or on the command line just type a question mark, followed by the function name, e.g. “?mean”
e. Web: Use www.rseek.org, instead of Google, because www.rseek.org does a Google search with non-R hits filtered out
FAQ’s
Q: Why use statistical software?
Because we want to analyze real data. Hand calculations on even moderate-size datasets is time consuming and can be infeasible. Also, allowing the computer to do the grunt-work allows us to give more attention to important concepts.
Q: Why use R instead of Excel, or some easier package?
R has become the academic standard statistical software and is the most widely used statistical software package in the world. R is free, while Excel, SPSS, StatCrunch, Minitab, etc. are not. R has the same interface for PC and Mac, (Excel does not and currently has 2 versions for PC and Mac, each making it difficult to teach in a cross-platform classroom). R, which is language-based, is more conducive to learning to think statistically than menu-based software such as SPSS or Minitab. Excel is statistically limited and inconsistent. R is extremely powerful, can produce publication quality graphics, and is a marketable skill.
Q: [Math 210 Intro to Prob & Stats & Math 318 Biostats] Why don’t we spend more time on R in class, or even have a separate lab?
The content of this course is fairly well-specified in universities across the country (this has implications for the transferability of the course). For schools that use software, they usually have a 4th or a 5th unit, which is an entire computer lab section. At Biola, however, the programs which require Math 210 IntroStat, Math 318 Biostats, & PHLT 515 Principles of Biostats do not want to encumber their programs with an extra unit. In addition, we are in a transitioning academic environment where over 95% of my students own their own laptop; they are rather computer literate; and distance learning is en vogue. This RStudio Master Plan, then, is my answer to the above factors – attempting to deliver the innovative power and education of R, in a semi-distance-learning manner, within a traditional statistics class. It adds some weight to the course, but I believe is worth it.