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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 19 Jan 2016 19:05:46 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Jan/19/t1453230353zvabjcs2c0tvj21.htm/, Retrieved Fri, 17 May 2024 11:40:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=289742, Retrieved Fri, 17 May 2024 11:40:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact188

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2016-01-19 19:05:46] [c1d30e054cfc8d57c9ede1dcf5423ffe] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.894
1.757
3.582
5.321
5.561
5.907
4.944
4.966
3.258
1.964
1.743
1.262
2.086
1.793
3.548
5.672
6.084
4.914
4.990
5.139
3.218
2.179
2.238
1.442
2.205
2.025
3.531
4.977
7.998
4.880
5.231
5.202
3.303
2.683
2.202
1.376
2.422
1.997
3.163
5.964
5.657
6.415
6.208
4.500
2.939
2.702
2.090
1.504
2.549
1.931
3.013
6.204
5.788
5.611
5.594
4.647
3.490
2.487
1.992
1.507
2.306
2.002
3.075
5.331
5.589
5.813
4.876
4.665
3.601
2.192
2.111
1.580
2.288
1.993
3.228
5.000
5.480
5.770
4.962
4.685
3.607
2.222
2.467
1.594
2.228
1.910
3.157
4.809
6.249
4.607
4.975
4.784
3.028
2.461
2.218
1.351
2.070
1.887
3.024
4.596
6.398
4.459
5.382
4.359
2.687
2.249
2.154
1.169
2.429
1.762
2.846
5.627
5.749
4.502
5.720
4.403
2.867
2.635
2.059
1.511
2.359
1.741
2.917
6.249
5.760
6.250
5.134
4.831
3.695
2.462
2.146
1.579

Tables (Output of Computation)





\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
R Engine error message & 
Error in hist.default(x, breaks = par1, col = par2, main = main, xlab = xlab,  : 
  some 'x' not counted; maybe 'breaks' do not span range of 'x'
Calls: hist -> hist.default
In addition: Warning messages:
1: In if (is.na(par1)) { :
  the condition has length > 1 and only the first element will be used
2: In if (par1 < 0) par1 <- 3 :
  the condition has length > 1 and only the first element will be used
3: In if (par1 > 50) par1 <- 50 :
  the condition has length > 1 and only the first element will be used
Execution halted

 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=289742&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[ROW][C]R Engine error message[/C][C]
Error in hist.default(x, breaks = par1, col = par2, main = main, xlab = xlab,  : 
  some 'x' not counted; maybe 'breaks' do not span range of 'x'
Calls: hist -> hist.default
In addition: Warning messages:
1: In if (is.na(par1)) { :
  the condition has length > 1 and only the first element will be used
2: In if (par1 < 0) par1 <- 3 :
  the condition has length > 1 and only the first element will be used
3: In if (par1 > 50) par1 <- 50 :
  the condition has length > 1 and only the first element will be used
Execution halted

[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=289742&T=0


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par2 = grey ; par3 = FALSE ; par4 = 7-point Likert ;
Parameters (R input):
par1 = ; par2 = grey ; par3 = FALSE ; par4 = 7-point Likert ;
R code (references can be found in the software module):
par4 <- '5-point Likert'
par3 <- 'FALSE'
par2 <- 'red'
par1 <- ''
par1 <- as.numeric(par1)
if (par3 == 'TRUE') par3 <- TRUE
if (par3 == 'FALSE') par3 <- FALSE
if (par4 == 'Unknown') par1 <- as.numeric(par1)
if (par4 == 'Interval/Ratio') par1 <- as.numeric(par1)
if (par4 == '3-point Likert') par1 <- c(1:3 - 0.5, 3.5)
if (par4 == '4-point Likert') par1 <- c(1:4 - 0.5, 4.5)
if (par4 == '5-point Likert') par1 <- c(1:5 - 0.5, 5.5)
if (par4 == '6-point Likert') par1 <- c(1:6 - 0.5, 6.5)
if (par4 == '7-point Likert') par1 <- c(1:7 - 0.5, 7.5)
if (par4 == '8-point Likert') par1 <- c(1:8 - 0.5, 8.5)
if (par4 == '9-point Likert') par1 <- c(1:9 - 0.5, 9.5)
if (par4 == '10-point Likert') par1 <- c(1:10 - 0.5, 10.5)
bitmap(file='test1.png')
if(is.numeric(x[1])) {
if (is.na(par1)) {
myhist<-hist(x,col=par2,main=main,xlab=xlab,right=par3)
} else {
if (par1 < 0) par1 <- 3
if (par1 > 50) par1 <- 50
myhist<-hist(x,breaks=par1,col=par2,main=main,xlab=xlab,right=par3)
}
} else {
barplot(mytab <- sort(table(x),T),col=par2,main='Frequency Plot',xlab=xlab,ylab='Absolute Frequency')
}
dev.off()
if(is.numeric(x[1])) {
myhist
n <- length(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('histogram.htm','Frequency Table (Histogram)',''),6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Bins',header=TRUE)
a<-table.element(a,'Midpoint',header=TRUE)
a<-table.element(a,'Abs. Frequency',header=TRUE)
a<-table.element(a,'Rel. Frequency',header=TRUE)
a<-table.element(a,'Cumul. Rel. Freq.',header=TRUE)
a<-table.element(a,'Density',header=TRUE)
a<-table.row.end(a)
crf <- 0
if (par3 == FALSE) mybracket <- '[' else mybracket <- ']'
mynumrows <- (length(myhist$breaks)-1)
for (i in 1:mynumrows) {
a<-table.row.start(a)
if (i == 1)
dum <- paste('[',myhist$breaks[i],sep='')
else
dum <- paste(mybracket,myhist$breaks[i],sep='')
dum <- paste(dum,myhist$breaks[i+1],sep=',')
if (i==mynumrows)
dum <- paste(dum,']',sep='')
else
dum <- paste(dum,mybracket,sep='')
a<-table.element(a,dum,header=TRUE)
a<-table.element(a,myhist$mids[i])
a<-table.element(a,myhist$counts[i])
rf <- myhist$counts[i]/n
crf <- crf + rf
a<-table.element(a,round(rf,6))
a<-table.element(a,round(crf,6))
a<-table.element(a,round(myhist$density[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
} else {
mytab
reltab <- mytab / sum(mytab)
n <- length(mytab)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Frequency Table (Categorical Data)',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Category',header=TRUE)
a<-table.element(a,'Abs. Frequency',header=TRUE)
a<-table.element(a,'Rel. Frequency',header=TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,labels(mytab)$x[i],header=TRUE)
a<-table.element(a,mytab[i])
a<-table.element(a,round(reltab[i],4))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}