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Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 26 Jan 2015 16:32:11 +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/2015/Jan/26/t14222899963f5tncs5b2315mm.htm/, Retrieved Tue, 14 May 2024 18:41:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=276169, Retrieved Tue, 14 May 2024 18:41:32 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact167
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2015-01-26 16:32:11] [006461bb825a57cb671d1f8ff85b37cb] [Current]
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Dataseries X:
299,81
299,01
296,82
296,67
296,95
296,80
296,80
295,93
293,77
291,02
288,61
284,55
284,55
278,14
273,28
270,14
268,36
267,15
267,15
265,47
261,75
256,51
252,98
251,17
251,17
244,27
240,54
238,92
237,47
235,91
235,91
231,41
224,94
222,19
219,06
217,83
217,83
216,89
213,84
212,90
213,98
215,31
215,31
214,09
213,71
211,54
209,40
207,33
207,33
202,75
200,26
198,99
198,82
198,43
198,43
195,68
195,45
193,65
191,38
189,71
189,71
185,49
183,01
182,38
181,60
182,13
182,13
180,81
180,25
179,84
178,50
178,11
178,11
178,10
177,52
177,34
175,53
176,01
175,94
175,47
175,48
173,76
173,74
173,65
172,00
171,50
170,41
171,50
171,43
170,69
170,40
169,90
170,21
170,55
169,98
169,34




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=276169&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=276169&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=276169&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[160,180[170270.281250.281250.014062
[180,200[190180.18750.468750.009375
[200,220[210170.1770830.6458330.008854
[220,240[23070.0729170.718750.003646
[240,260[25060.06250.781250.003125
[260,280[27080.0833330.8645830.004167
[280,300]290130.13541710.006771

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[160,180[ & 170 & 27 & 0.28125 & 0.28125 & 0.014062 \tabularnewline
[180,200[ & 190 & 18 & 0.1875 & 0.46875 & 0.009375 \tabularnewline
[200,220[ & 210 & 17 & 0.177083 & 0.645833 & 0.008854 \tabularnewline
[220,240[ & 230 & 7 & 0.072917 & 0.71875 & 0.003646 \tabularnewline
[240,260[ & 250 & 6 & 0.0625 & 0.78125 & 0.003125 \tabularnewline
[260,280[ & 270 & 8 & 0.083333 & 0.864583 & 0.004167 \tabularnewline
[280,300] & 290 & 13 & 0.135417 & 1 & 0.006771 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=276169&T=1

[TABLE]
[ROW][C]Frequency Table (Histogram)[/C][/ROW]
[ROW][C]Bins[/C][C]Midpoint[/C][C]Abs. Frequency[/C][C]Rel. Frequency[/C][C]Cumul. Rel. Freq.[/C][C]Density[/C][/ROW]
[ROW][C][160,180[[/C][C]170[/C][C]27[/C][C]0.28125[/C][C]0.28125[/C][C]0.014062[/C][/ROW]
[ROW][C][180,200[[/C][C]190[/C][C]18[/C][C]0.1875[/C][C]0.46875[/C][C]0.009375[/C][/ROW]
[ROW][C][200,220[[/C][C]210[/C][C]17[/C][C]0.177083[/C][C]0.645833[/C][C]0.008854[/C][/ROW]
[ROW][C][220,240[[/C][C]230[/C][C]7[/C][C]0.072917[/C][C]0.71875[/C][C]0.003646[/C][/ROW]
[ROW][C][240,260[[/C][C]250[/C][C]6[/C][C]0.0625[/C][C]0.78125[/C][C]0.003125[/C][/ROW]
[ROW][C][260,280[[/C][C]270[/C][C]8[/C][C]0.083333[/C][C]0.864583[/C][C]0.004167[/C][/ROW]
[ROW][C][280,300][/C][C]290[/C][C]13[/C][C]0.135417[/C][C]1[/C][C]0.006771[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=276169&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=276169&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[160,180[170270.281250.281250.014062
[180,200[190180.18750.468750.009375
[200,220[210170.1770830.6458330.008854
[220,240[23070.0729170.718750.003646
[240,260[25060.06250.781250.003125
[260,280[27080.0833330.8645830.004167
[280,300]290130.13541710.006771



Parameters (Session):
par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
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 {
plot(mytab <- table(x),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')
}