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Statistical Analysis

Statistical Analysis. Programming in R. Vectors and assignment. Simplest data structure is the numeric vector: Type at the command line: > x<-c(10.4, 5.6, 3.1, 6.4, 21.7) Type x at the command line to see the result: > x [1] 10.4 5.6 3.1 6.4 21.7 >. c() is a function.

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Statistical Analysis

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  1. Statistical Analysis Programming in R

  2. Vectors and assignment • Simplest data structure is the numeric vector: • Type at the command line: > x<-c(10.4, 5.6, 3.1, 6.4, 21.7) • Type x at the command line to see the result: > x [1] 10.4 5.6 3.1 6.4 21.7 >

  3. c() is a function • Function c() takes an arbitrary number of vector arguments and concatenates them. > y<-c(x, 0, x) > y [1] 10.4 5.6 3.1 6.4 21.7 0.0 10.4 5.6 3.1 6.4 21.7

  4. Vector arithmetic • +,x,*,/,^ • log, exp, sin, cos, tan, sqrt,… • max, min, range • length, sum, prod

  5. Calculate mean in R: mean and variation > mean(x) [1] 9.44 > > var(x) [1] 53.853 >

  6. Calculate mean in R: mean and variation • mean(x) can be written as: > sum(x)/length(x) [1] 9.44 • var(x) can be written as: > sum((x-mean(x))^2)/(length(x)-1) [1] 53.853

  7. Two sample t-statistic twosam = function(y1,y2) { n1=length(y1); n2 =length(y2) yb1=mean(y1); yb2=mean(y2) s1=var(y1); s2=var(y2) s=((n1-1)*s1 + (n2-1)*s2)/(n1+n2-2) tst=(yb1-yb2)/sqrt(s2*(1/n1+1/n2)) tst } Copy and paste the above statements onto the command line in R

  8. Should look like this: > twosam <- function(y1,y2) { + n1<-length(y1); n2 <-length(y2) + yb1=mean(y1); yb2=mean(y2) + s1=var(y1); s2=var(y2) + s=((n1-1)*s1 + (n2-1)*s2)/(n1+n2-2) + tst=(yb1-yb2)/sqrt(s2*(1/n1+1/n2)) + tst + }

  9. Test your function by calling it: > tstat=twosam(x,x+1) > tstat [1] -0.2154592 >

  10. Generating regular sequences • 1:30 is the same with c(1,2,3,…,29,30) • : operator has the highest priority within an expression. For example: > 2*1:5 [1] 2 4 6 8 10

  11. factors > codons=c("GCA","GCC","GCG","GCU","UGC","UGU") > codons [1] "GCA" "GCC" "GCG" "GCU" "UGC" "UGU" > aminoacids=c("Ala","Ala","Ala","Ala","Cys","Cys") > aminoacids [1] "Ala" "Ala" "Ala" "Ala" "Cys" "Cys" > aaf=factor(aminoacids) > aaf [1] Ala Ala Ala Ala Cys Cys Levels: Ala Cys > ii=tapply(codons,aaf,print) [1] "GCA" "GCC" "GCG" "GCU" [1] "UGC" "UGU" >

  12. arrays > x=array(1:20,dim=c(4,5)) > x [,1] [,2] [,3] [,4] [,5] [1,] 1 5 9 13 17 [2,] 2 6 10 14 18 [3,] 3 7 11 15 19 [4,] 4 8 12 16 20

  13. arrays > x=array(0,dim=c(4,5)) > x [,1] [,2] [,3] [,4] [,5] [1,] 0 0 0 0 0 [2,] 0 0 0 0 0 [3,] 0 0 0 0 0 [4,] 0 0 0 0 0 >

  14. Indexing arrays > i=array(c(1:3,3:1),dim=c(3,2)) > i [,1] [,2] [1,] 1 3 [2,] 2 2 [3,] 3 1 > x=array(1:20,dim=c(4,5)) > x [,1] [,2] [,3] [,4] [,5] [1,] 1 5 9 13 17 [2,] 2 6 10 14 18 [3,] 3 7 11 15 19 [4,] 4 8 12 16 20 > x[i] [1] 9 6 3 > x[i]=0 > x [,1] [,2] [,3] [,4] [,5] [1,] 1 5 0 13 17 [2,] 2 0 10 14 18 [3,] 0 7 11 15 19 [4,] 4 8 12 16 20

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