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![Vectors
Try: c(3,5,7)
Try: c(‘s’,’a’,’a’,’d’)
Try: 3:7
Try: seq(3,7)
Try: seq(3,7,0.25)
Try: 7:3
Try: name <-c(‘s’,’a’,’a’,’d’)’
Try: name [3]
Try: name [3] <- ‘d’
Try: name [4] <- ‘e’
Try: name](https://image.slidesharecdn.com/csse2014rworkshoptaed1-140526000456-phpapp01/75/R-Intro-Workshop-9-2048.jpg)
![Vectors Names
Try: ranks <- 1:3
Try: names (ranks) <- c(“1st”,”2nd”,”3rd”, )
Try: ranks
Try: ranks [first]
Try: ranks [3] <-4
Try: scoRes <- c(450,578,502)
Try: barplot(scoRes)
Try: names(scoRes) <- c(“Bob”, “Marry”, “Jane”)
Try: barplot (1:200)](https://image.slidesharecdn.com/csse2014rworkshoptaed1-140526000456-phpapp01/75/R-Intro-Workshop-10-2048.jpg)
![Access Values
Try: print(seats)
Try: seats[2,3]
Try: seats[2,]
Try: seats[1,]
Try: seats[,3]
Try: seats[,5:9]](https://image.slidesharecdn.com/csse2014rworkshoptaed1-140526000456-phpapp01/75/R-Intro-Workshop-12-2048.jpg)
![Matrix
Try: MATD <-matrix(1:6,2)
Try: MATE <-matrix(c(rep(1,3), rep(2,3)), 2, byrow=T)
Try: MATE+MATD
Try: MATD+10
Try: MATD-10
Try: MATD+10
Try: MATD
Try: MATE-MATE
Try: MATD-MATE
Try: solve(MATD[,2:3])
Try: t(MATE)
Try: MATD %*% t(MATE)
Try: MATD*100
Try: MATD/MATE](https://image.slidesharecdn.com/csse2014rworkshoptaed1-140526000456-phpapp01/75/R-Intro-Workshop-13-2048.jpg)
![Vectors
Try: c(3,5,7)
Try: c(‘s’,’a’,’a’,’d’)
Try: 3:7
Try: seq(3,7)
Try: seq(3,7,0.25)
Try: 7:3
Try: name <-c(‘s’,’a’,’a’,’d’)’
Try: name [3]
Try: name [3] <- ‘d’
Try: name [4] <- ‘e’
Try: name](https://crownmelresort.com/image.slidesharecdn.com/csse2014rworkshoptaed1-140526000456-phpapp01/75/R-Intro-Workshop-9-2048.jpg)
![Vectors Names
Try: ranks <- 1:3
Try: names (ranks) <- c(“1st”,”2nd”,”3rd”, )
Try: ranks
Try: ranks [first]
Try: ranks [3] <-4
Try: scoRes <- c(450,578,502)
Try: barplot(scoRes)
Try: names(scoRes) <- c(“Bob”, “Marry”, “Jane”)
Try: barplot (1:200)](https://crownmelresort.com/image.slidesharecdn.com/csse2014rworkshoptaed1-140526000456-phpapp01/75/R-Intro-Workshop-10-2048.jpg)
![Access Values
Try: print(seats)
Try: seats[2,3]
Try: seats[2,]
Try: seats[1,]
Try: seats[,3]
Try: seats[,5:9]](https://crownmelresort.com/image.slidesharecdn.com/csse2014rworkshoptaed1-140526000456-phpapp01/75/R-Intro-Workshop-12-2048.jpg)
![Matrix
Try: MATD <-matrix(1:6,2)
Try: MATE <-matrix(c(rep(1,3), rep(2,3)), 2, byrow=T)
Try: MATE+MATD
Try: MATD+10
Try: MATD-10
Try: MATD+10
Try: MATD
Try: MATE-MATE
Try: MATD-MATE
Try: solve(MATD[,2:3])
Try: t(MATE)
Try: MATD %*% t(MATE)
Try: MATD*100
Try: MATD/MATE](https://crownmelresort.com/image.slidesharecdn.com/csse2014rworkshoptaed1-140526000456-phpapp01/75/R-Intro-Workshop-13-2048.jpg)
Uploaded bySaad Chahine
R Intro Workshop
This document provides an introduction to using R for statistical analysis. It outlines how to get started with R, perform basic calculations and logic, work with variables, vectors, matrices and factors. It also demonstrates how to import and export data, call data within R, and describes some useful R packages. Examples are provided for each concept to help users get hands-on experience with the R programming language.
More Related Content
R Intro Workshop
- 1. Intro Workshop Saad Chahine,PhD. May 26, 2014
- 2. What is R? “Ris a language and environment for statistical computing and graphics… similar to the S language and environment which was developed at Bell Laboratories… by John Chambers and colleagues…” “R is available as Free Software under the terms of the Free Software Foundation's GNU General Public Licenses in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.” http://www.r-project.org/
- 3. Getting Started • Download and launchR • Type help() press enter
- 4. Calculator ‘>’ is theprompt line Try: 3+5 Try: 3-5 Try: 3/5 Try: 3*5 Try: sqrt(5) Try: sum (1,3,5)
- 5. Logic ‘>’ is theprompt line Try: 3<5 Try: 3>5 Try: 3+5==8 Try: 3+5==9
- 6. Variables ‘<-’ assigns avalue Try: x<-24 Try: x Try: x/2 Try: x Try: x<-“hello world” Try: x Try: x<-T Try: x
- 7. Menu Bar • Savingyour documents • Working directories getwd() • Saving workspace
- 8. Help Example Try: help(ave) Try:help(mean) Try: help(mode) Try: help(median) Try: help(sd) Try: help(t.test) Try: help(anova) Try: example(ave) Try: example(mean) Try: example(mode) Try: example(median) Try: example(sd) Try: example(t.test) Try: example(anova)
- 9. Vectors Try: c(3,5,7) Try: c(‘s’,’a’,’a’,’d’) Try:3:7 Try: seq(3,7) Try: seq(3,7,0.25) Try: 7:3 Try: name <-c(‘s’,’a’,’a’,’d’)’ Try: name [3] Try: name [3] <- ‘d’ Try: name [4] <- ‘e’ Try: name
- 10. Vectors Names Try: ranks<- 1:3 Try: names (ranks) <- c(“1st”,”2nd”,”3rd”, ) Try: ranks Try: ranks [first] Try: ranks [3] <-4 Try: scoRes <- c(450,578,502) Try: barplot(scoRes) Try: names(scoRes) <- c(“Bob”, “Marry”, “Jane”) Try: barplot (1:200)
- 11. Matrices Try: matrix(0,6,7) Try: a<-1:42 Try:print (a) Try: matrix(a,6,7) Try: seats <- 1:20 Try: dim(seats) <- c(2,10) Try: print (seats)
- 12. Access Values Try: print(seats) Try:seats[2,3] Try: seats[2,] Try: seats[1,] Try: seats[,3] Try: seats[,5:9]
- 13. Matrix Try: MATD <-matrix(1:6,2) Try:MATE <-matrix(c(rep(1,3), rep(2,3)), 2, byrow=T) Try: MATE+MATD Try: MATD+10 Try: MATD-10 Try: MATD+10 Try: MATD Try: MATE-MATE Try: MATD-MATE Try: solve(MATD[,2:3]) Try: t(MATE) Try: MATD %*% t(MATE) Try: MATD*100 Try: MATD/MATE
- 14. Factors Try: data =c(1,2,2,3,1,3,2,2,3,3,3,2,2,1,2) Try: fdata=factor(data) Try: fdata Try: mean(data)
- 15. Import Data CSV 1.Find the file path 2. mydata <-read.table(”filepath”, header=T, sep=“,”) 3. mydata <-read.table(”filepath”, header=T, sep=“t”) 4. For fixed width use read.fwf
- 16. Import Data SPSS 1.Install.packages(“me misc”) 2. library(“memisc”) 3. mydata <- as.data.set(spss.syst em.file('/CSSE R Workshop/GEDU6100 dataset.sav')) 4. mydata
- 17.
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- 19.
- 20. Ways of callingyour data - Mean (mydata$MATH) - With(mydata, mean(MATH)) - t.test(MATH~GENDER, data=mydata)
- 21.
- 22. Export write.table(mydata, “filepath/mydata.txt”) Note: for exportto exl, SAS, SPSS you may need to use foreign package.
- 23. On your own Try:data() - Find a data set and str, summary & one statistical application
- 24.
- 25. Try this lastone… Try: contour(volcano) Try: persp(volcano, expand=0.2)
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- 27.