R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- array(list('g'
+ ,'Both'
+ ,'g'
+ ,'Physical'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Physical'
+ ,'b'
+ ,'Physical'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Both'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Mental'
+ ,'b'
+ ,'Both'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Both'
+ ,'b'
+ ,'Not_bul'
+ ,'b'
+ ,'Mental'
+ ,'b'
+ ,'Both'
+ ,'b'
+ ,'Both'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Both'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Both'
+ ,'g'
+ ,'Physical'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Both'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Physical'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Both'
+ ,'b'
+ ,'Physical'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Both'
+ ,'b'
+ ,'Both'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Mental'
+ ,'b'
+ ,'Mental'
+ ,'b'
+ ,'Physical'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Both'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Mental'
+ ,'b'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Physical'
+ ,'b'
+ ,'Not_bul'
+ ,'b'
+ ,'Physical'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Mental'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Both'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Mental'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Physical'
+ ,'g'
+ ,'Both'
+ ,'g'
+ ,'Physical'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Both'
+ ,'b'
+ ,'Not_bul'
+ ,'b'
+ ,'Physical'
+ ,'b'
+ ,'Both'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Both'
+ ,'b'
+ ,'Both'
+ ,'b'
+ ,'Physical'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Physical'
+ ,'g'
+ ,'Both'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Physical'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Both'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Not_bul'
+ ,'b'
+ ,'Both'
+ ,'g'
+ ,'Both'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Both'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Mental'
+ ,'b'
+ ,'Physical'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Both'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Physical'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Physical'
+ ,'g'
+ ,'Both'
+ ,'b'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Mental'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Mental'
+ ,'b'
+ ,'Physical'
+ ,'g'
+ ,'Mental'
+ ,'g'
+ ,'Both'
+ ,'b'
+ ,'Not_bul'
+ ,'g'
+ ,'Not_bul'
+ ,'b'
+ ,'Not_bul')
+ ,dim=c(2
+ ,193)
+ ,dimnames=list(c('gender'
+ ,'type_of_bullying')
+ ,1:193))
>  y <- array(NA,dim=c(2,193),dimnames=list(c('gender','type_of_bullying'),1:193))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
There were 50 or more warnings (use warnings() to see the first 50)
> par3 = 'Pearson Chi-Square'
> par2 = '2'
> par1 = '1'
> cat1 <- as.numeric(par1) #
> cat2<- as.numeric(par2) #
> simulate.p.value=FALSE
> if (par3 == 'Exact Pearson Chi Square by simulation') simulate.p.value=TRUE
> x <- t(x)
> (z <- array(unlist(x),dim=c(length(x[,1]),length(x[1,]))))
       [,1] [,2]      
  [1,] "g"  "Both"    
  [2,] "g"  "Physical"
  [3,] "g"  "Mental"  
  [4,] "g"  "Mental"  
  [5,] "b"  "Physical"
  [6,] "b"  "Physical"
  [7,] "b"  "Not_bul" 
  [8,] "g"  "Not_bul" 
  [9,] "g"  "Not_bul" 
 [10,] "b"  "Mental"  
 [11,] "g"  "Not_bul" 
 [12,] "b"  "Mental"  
 [13,] "g"  "Mental"  
 [14,] "b"  "Both"    
 [15,] "g"  "Not_bul" 
 [16,] "g"  "Mental"  
 [17,] "b"  "Mental"  
 [18,] "b"  "Both"    
 [19,] "b"  "Mental"  
 [20,] "g"  "Not_bul" 
 [21,] "b"  "Not_bul" 
 [22,] "b"  "Not_bul" 
 [23,] "g"  "Not_bul" 
 [24,] "g"  "Mental"  
 [25,] "b"  "Both"    
 [26,] "b"  "Not_bul" 
 [27,] "b"  "Mental"  
 [28,] "b"  "Both"    
 [29,] "b"  "Both"    
 [30,] "g"  "Not_bul" 
 [31,] "b"  "Both"    
 [32,] "g"  "Mental"  
 [33,] "b"  "Both"    
 [34,] "g"  "Physical"
 [35,] "b"  "Not_bul" 
 [36,] "g"  "Not_bul" 
 [37,] "b"  "Mental"  
 [38,] "g"  "Mental"  
 [39,] "b"  "Not_bul" 
 [40,] "g"  "Not_bul" 
 [41,] "g"  "Not_bul" 
 [42,] "b"  "Not_bul" 
 [43,] "g"  "Both"    
 [44,] "g"  "Not_bul" 
 [45,] "b"  "Not_bul" 
 [46,] "g"  "Not_bul" 
 [47,] "b"  "Physical"
 [48,] "g"  "Not_bul" 
 [49,] "g"  "Mental"  
 [50,] "g"  "Both"    
 [51,] "b"  "Physical"
 [52,] "g"  "Not_bul" 
 [53,] "b"  "Not_bul" 
 [54,] "g"  "Mental"  
 [55,] "b"  "Not_bul" 
 [56,] "b"  "Not_bul" 
 [57,] "g"  "Not_bul" 
 [58,] "g"  "Mental"  
 [59,] "g"  "Not_bul" 
 [60,] "g"  "Not_bul" 
 [61,] "g"  "Mental"  
 [62,] "g"  "Mental"  
 [63,] "b"  "Both"    
 [64,] "b"  "Both"    
 [65,] "g"  "Not_bul" 
 [66,] "b"  "Mental"  
 [67,] "g"  "Mental"  
 [68,] "b"  "Mental"  
 [69,] "b"  "Mental"  
 [70,] "b"  "Physical"
 [71,] "g"  "Mental"  
 [72,] "b"  "Not_bul" 
 [73,] "g"  "Not_bul" 
 [74,] "b"  "Not_bul" 
 [75,] "g"  "Both"    
 [76,] "g"  "Mental"  
 [77,] "g"  "Mental"  
 [78,] "b"  "Mental"  
 [79,] "b"  "Not_bul" 
 [80,] "b"  "Not_bul" 
 [81,] "b"  "Mental"  
 [82,] "g"  "Not_bul" 
 [83,] "g"  "Mental"  
 [84,] "g"  "Mental"  
 [85,] "g"  "Physical"
 [86,] "b"  "Not_bul" 
 [87,] "b"  "Physical"
 [88,] "g"  "Mental"  
 [89,] "b"  "Mental"  
 [90,] "b"  "Mental"  
 [91,] "g"  "Mental"  
 [92,] "g"  "Mental"  
 [93,] "b"  "Not_bul" 
 [94,] "g"  "Not_bul" 
 [95,] "b"  "Not_bul" 
 [96,] "g"  "Mental"  
 [97,] "g"  "Not_bul" 
 [98,] "g"  "Mental"  
 [99,] "g"  "Both"    
[100,] "g"  "Mental"  
[101,] "g"  "Not_bul" 
[102,] "g"  "Not_bul" 
[103,] "b"  "Not_bul" 
[104,] "g"  "Mental"  
[105,] "g"  "Mental"  
[106,] "b"  "Mental"  
[107,] "b"  "Not_bul" 
[108,] "g"  "Not_bul" 
[109,] "b"  "Physical"
[110,] "g"  "Both"    
[111,] "g"  "Physical"
[112,] "b"  "Not_bul" 
[113,] "g"  "Not_bul" 
[114,] "b"  "Both"    
[115,] "b"  "Not_bul" 
[116,] "b"  "Physical"
[117,] "b"  "Both"    
[118,] "g"  "Not_bul" 
[119,] "g"  "Both"    
[120,] "b"  "Both"    
[121,] "b"  "Physical"
[122,] "g"  "Not_bul" 
[123,] "g"  "Not_bul" 
[124,] "g"  "Mental"  
[125,] "g"  "Mental"  
[126,] "g"  "Not_bul" 
[127,] "b"  "Mental"  
[128,] "g"  "Mental"  
[129,] "g"  "Not_bul" 
[130,] "b"  "Mental"  
[131,] "g"  "Physical"
[132,] "g"  "Both"    
[133,] "g"  "Not_bul" 
[134,] "g"  "Not_bul" 
[135,] "b"  "Not_bul" 
[136,] "g"  "Mental"  
[137,] "b"  "Physical"
[138,] "b"  "Mental"  
[139,] "g"  "Mental"  
[140,] "g"  "Not_bul" 
[141,] "b"  "Both"    
[142,] "g"  "Mental"  
[143,] "b"  "Mental"  
[144,] "g"  "Mental"  
[145,] "g"  "Mental"  
[146,] "b"  "Not_bul" 
[147,] "g"  "Not_bul" 
[148,] "g"  "Mental"  
[149,] "b"  "Not_bul" 
[150,] "b"  "Both"    
[151,] "g"  "Both"    
[152,] "g"  "Not_bul" 
[153,] "g"  "Not_bul" 
[154,] "b"  "Not_bul" 
[155,] "g"  "Not_bul" 
[156,] "g"  "Not_bul" 
[157,] "g"  "Not_bul" 
[158,] "b"  "Both"    
[159,] "b"  "Mental"  
[160,] "g"  "Not_bul" 
[161,] "b"  "Mental"  
[162,] "g"  "Not_bul" 
[163,] "b"  "Mental"  
[164,] "b"  "Physical"
[165,] "b"  "Mental"  
[166,] "g"  "Not_bul" 
[167,] "b"  "Mental"  
[168,] "g"  "Both"    
[169,] "b"  "Not_bul" 
[170,] "g"  "Not_bul" 
[171,] "b"  "Not_bul" 
[172,] "b"  "Not_bul" 
[173,] "g"  "Not_bul" 
[174,] "g"  "Mental"  
[175,] "b"  "Physical"
[176,] "b"  "Mental"  
[177,] "g"  "Mental"  
[178,] "g"  "Not_bul" 
[179,] "b"  "Physical"
[180,] "g"  "Both"    
[181,] "b"  "Not_bul" 
[182,] "b"  "Not_bul" 
[183,] "g"  "Mental"  
[184,] "b"  "Mental"  
[185,] "g"  "Not_bul" 
[186,] "b"  "Not_bul" 
[187,] "g"  "Mental"  
[188,] "b"  "Physical"
[189,] "g"  "Mental"  
[190,] "g"  "Both"    
[191,] "b"  "Not_bul" 
[192,] "g"  "Not_bul" 
[193,] "b"  "Not_bul" 
> (table1 <- table(z[,cat1],z[,cat2]))
   
    Both Mental Not_bul Physical
  b   15     25      34       14
  g   12     40      48        5
> (V1<-dimnames(y)[[1]][cat1])
[1] "gender"
> (V2<-dimnames(y)[[1]][cat2])
[1] "type_of_bullying"
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Tabulation of Results',ncol(table1)+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, ' ', 1,TRUE)
> for(nc in 1:ncol(table1)){
+ a<-table.element(a, colnames(table1)[nc], 1, TRUE)
+ }
> a<-table.row.end(a)
> for(nr in 1:nrow(table1) ){
+ a<-table.element(a, rownames(table1)[nr], 1, TRUE)
+ for(nc in 1:ncol(table1) ){
+ a<-table.element(a, table1[nr, nc], 1, FALSE)
+ }
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14u4a1386632768.tab") 
> (cst<-chisq.test(table1, simulate.p.value=simulate.p.value) )

	Pearson's Chi-squared test

data:  table1
X-squared = 9.0209, df = 3, p-value = 0.02901

> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Tabulation of Expected Results',ncol(table1)+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, ' ', 1,TRUE)
> for(nc in 1:ncol(table1)){
+ a<-table.element(a, colnames(table1)[nc], 1, TRUE)
+ }
> a<-table.row.end(a)
> for(nr in 1:nrow(table1) ){
+ a<-table.element(a, rownames(table1)[nr], 1, TRUE)
+ for(nc in 1:ncol(table1) ){
+ a<-table.element(a, round(cst$expected[nr, nc], digits=2), 1, FALSE)
+ }
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/2cbgf1386632768.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Statistical Results',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, cst$method, 2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Chi Square Statistic', 1, TRUE)
> a<-table.element(a, round(cst$statistic, digits=2), 1,FALSE)
> a<-table.row.end(a)
> if(!simulate.p.value){
+ a<-table.row.start(a)
+ a<-table.element(a, 'Degrees of Freedom', 1, TRUE)
+ a<-table.element(a, cst$parameter, 1,FALSE)
+ a<-table.row.end(a)
+ }
> a<-table.row.start(a)
> a<-table.element(a, 'P value', 1, TRUE)
> a<-table.element(a, round(cst$p.value, digits=2), 1,FALSE)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/31khh1386632768.tab") 
> 
> 
> 
> proc.time()
   user  system elapsed 
  0.933   0.387   1.283