1. Using R for Statistical Instruction
Getting Started
By Buddy Bilbrey, Lander University

2. Advantages of R Open source (free)
(2016) KD Nuggets survey stated that R is the top software among professionals
Industry Professionals are using because of price and capabilities
Extremely powerful (many different contributors)
Stable on virtually any platform
Performs more than statistics (data mining and other analytic functions)
Gives students a skill that is extremely desirable

3. Disadvantages of R STEEP learning curve
Uses typed commands instead of GUI
Newer versions sometimes force upgrading the software
No warranty or defined help available (must use the web)
Solutions are difficult to find due to limited online examples (this gets better every day)

4. Finding and Installing the Software
Must choose a mirror site for downloading
Must add each package individually
Throwback to 90’s command line software

5. Downloading R

6.
All mirror sites have identical copies
This prevents one server from becoming overloaded

7. Mirror Sites List by Country

8. From inside the R Software – select mirror sites for each new package installed

9. List of Mirror Sites by country

10. List of Packages Available for Installing

11. Some Available GUIs R-Commander (most common) Sciviews-K RKWard PMG
Red-R
R Analytic Flow

12. R-Commander (GUI) Must be installed separately as a package
Very common commands included
Does graphing including 3D graphics
Incomplete
Some commands need to ran in R on command line
Other packages may need to be installed (qcc (quality control), DOE, etc.)
Unavailable functions are greyed out automatically
NOTE: It is difficult to go from a GUI to typing in commands on command line

13. Opening R-Commander (case sensitive)
Type the following AFTER the Rcmdr package is installed in R > library(Rcmdr)

14. R-Commander Examples

15. Importing Data into Rcmdr
Can import from clipboard
Can import from files
Can copy/paste from clipboard
.csv files work best for importing entire file
Excel files sometimes are difficult

16. Importing into Rcmdr with Clipboard or file
Name the
Dataset for later referencing
Clipboard or
.csv file

17. Reference Books for use with R instruction
R for Business Analytics by A. Ohri (recommended for beginners)
Business Analytics for Managers by Wolfgang Jank
An Introduction to Statistical Learning (ISLR) –
Free .pdf book (advanced Analytics)
( ) which takes you to -> ( bcf.usc.edu/~gareth/ISL/ )

18. ISLR Online Book
eBook
.pdf
download

19. ISLR Basic Commands 2.3.1 type in single column of data
> x = c(1,6,2) # stores the three values in variable x
> y = c(1,4,3) # stores the three values in variable y
> x # print values stored in x
[1] 1 6 2
> length(x) # number of values in x
[1] 3

20. ISLR Basic Commands 2.3.1 (cont.’)
> x=matrix (data=c(1,2,3,4) , nrow=2, ncol =2) # create a table of data > x [,1] [,2] [1,] 1 3 [2,] 2 4

21. ISLR Basic Commands 2.3.1 (cont.’)
> sqrt(x) # take the square root and square values [,1] [,2] [1,] [2,] > x^2 [1,] 1 9 [2,] 4 16

22. Other Common Commands
[Create a linear regression model* – store in variable model1]
> priceData <- read.csv(file.choose()) # input the data with dialog
> priceModel <- lm(Price~Qty, data = priceData) # build the regression model
> summary(priceModel) # print the results
Data came from “Business Analytics for Managers” by Wolfgang Jank.

23. Experiences with Teaching Statistics in R
Small bite examples (one-sample t-test, two-sample t-test, regression, etc.)
Students actually retain the commands well with practice
Difficult to go backwards from GUI to command lines