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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 23 Sep 2013 05:35:34 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Sep/23/t1379928961nvmzwrai4mz5ew6.htm/, Retrieved Tue, 10 Feb 2026 15:11:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=211745, Retrieved Tue, 10 Feb 2026 15:11:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact411

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [] [2013-09-23 08:02:05] [9fb2675916b8773bb0a74f31adc60d44]
- R P     [Histogram] [] [2013-09-23 09:35:34] [79b59004c90874912279e9b1431bd052] [Current]
- RMP       [Quartiles] [] [2013-09-30 11:27:45] [9fb2675916b8773bb0a74f31adc60d44]
- RMPD      [Notched Boxplots] [] [2013-09-30 11:44:33] [9fb2675916b8773bb0a74f31adc60d44]
- R  D        [Notched Boxplots] [] [2013-10-03 13:16:19] [74be16979710d4c4e7c6647856088456]
- RMPD      [Notched Boxplots] [] [2013-09-30 11:46:25] [9fb2675916b8773bb0a74f31adc60d44]
- R  D        [Notched Boxplots] [] [2013-10-03 13:10:30] [74be16979710d4c4e7c6647856088456]
-    D          [Notched Boxplots] [] [2013-10-07 06:29:47] [74be16979710d4c4e7c6647856088456]
- R  D            [Notched Boxplots] [] [2013-10-07 08:04:23] [9fb2675916b8773bb0a74f31adc60d44]
- RMPD            [Central Tendency] [] [2013-10-07 08:06:46] [9fb2675916b8773bb0a74f31adc60d44]
- RMPD            [Mean versus Median] [] [2013-10-07 08:10:28] [9fb2675916b8773bb0a74f31adc60d44]
- RMPD            [Central Tendency] [] [2013-10-07 08:22:09] [9fb2675916b8773bb0a74f31adc60d44]
- RMPD            [Mean versus Median] [] [2013-10-07 08:24:47] [9fb2675916b8773bb0a74f31adc60d44]
- RMPD          [Harrell-Davis Quantiles] [] [2013-10-07 06:34:33] [9fb2675916b8773bb0a74f31adc60d44]
- R PD            [Harrell-Davis Quantiles] [] [2013-12-28 12:08:29] [74be16979710d4c4e7c6647856088456]
- RMPD          [Harrell-Davis Quantiles] [] [2013-10-07 06:43:36] [9fb2675916b8773bb0a74f31adc60d44]
- RMPD          [Harrell-Davis Quantiles] [] [2013-10-07 06:46:31] [9fb2675916b8773bb0a74f31adc60d44]
- RMPD      [Harrell-Davis Quantiles] [] [2013-09-30 11:52:53] [9fb2675916b8773bb0a74f31adc60d44]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
80
80
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80
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Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211745&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211745&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211745&T=0

As an alternative you can also use a QR Code:  
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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[80,85[82.5140.0915030.0915030.018301
[85,90[87.5220.1437910.2352940.028758
[90,95[92.5660.4313730.6666670.086275
[95,100[97.5000.6666670
[100,105[102.5150.0980390.7647060.019608
[105,110[107.5000.7647060
[110,115[112.5130.0849670.8496730.016993
[115,120[117.5000.8496730
[120,125[122.5210.1372550.9869280.027451
[125,130[127.5000.9869280
[130,135[132.5000.9869280
[135,140[137.5000.9869280
[140,145[142.5000.9869280
[145,150[147.5000.9869280
[150,155[152.5000.9869280
[155,160[157.5000.9869280
[160,165[162.5000.9869280
[165,170[167.5000.9869280
[170,175[172.5000.9869280
[175,180[177.5000.9869280
[180,185[182.5000.9869280
[185,190[187.5000.9869280
[190,195[192.5000.9869280
[195,200[197.5000.9869280
[200,205[202.510.0065360.9934640.001307
[205,210]207.510.00653610.001307

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[80,85[ & 82.5 & 14 & 0.091503 & 0.091503 & 0.018301 \tabularnewline
[85,90[ & 87.5 & 22 & 0.143791 & 0.235294 & 0.028758 \tabularnewline
[90,95[ & 92.5 & 66 & 0.431373 & 0.666667 & 0.086275 \tabularnewline
[95,100[ & 97.5 & 0 & 0 & 0.666667 & 0 \tabularnewline
[100,105[ & 102.5 & 15 & 0.098039 & 0.764706 & 0.019608 \tabularnewline
[105,110[ & 107.5 & 0 & 0 & 0.764706 & 0 \tabularnewline
[110,115[ & 112.5 & 13 & 0.084967 & 0.849673 & 0.016993 \tabularnewline
[115,120[ & 117.5 & 0 & 0 & 0.849673 & 0 \tabularnewline
[120,125[ & 122.5 & 21 & 0.137255 & 0.986928 & 0.027451 \tabularnewline
[125,130[ & 127.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[130,135[ & 132.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[135,140[ & 137.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[140,145[ & 142.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[145,150[ & 147.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[150,155[ & 152.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[155,160[ & 157.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[160,165[ & 162.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[165,170[ & 167.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[170,175[ & 172.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[175,180[ & 177.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[180,185[ & 182.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[185,190[ & 187.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[190,195[ & 192.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[195,200[ & 197.5 & 0 & 0 & 0.986928 & 0 \tabularnewline
[200,205[ & 202.5 & 1 & 0.006536 & 0.993464 & 0.001307 \tabularnewline
[205,210] & 207.5 & 1 & 0.006536 & 1 & 0.001307 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211745&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][80,85[[/C][C]82.5[/C][C]14[/C][C]0.091503[/C][C]0.091503[/C][C]0.018301[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]22[/C][C]0.143791[/C][C]0.235294[/C][C]0.028758[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]66[/C][C]0.431373[/C][C]0.666667[/C][C]0.086275[/C][/ROW]
[ROW][C][95,100[[/C][C]97.5[/C][C]0[/C][C]0[/C][C]0.666667[/C][C]0[/C][/ROW]
[ROW][C][100,105[[/C][C]102.5[/C][C]15[/C][C]0.098039[/C][C]0.764706[/C][C]0.019608[/C][/ROW]
[ROW][C][105,110[[/C][C]107.5[/C][C]0[/C][C]0[/C][C]0.764706[/C][C]0[/C][/ROW]
[ROW][C][110,115[[/C][C]112.5[/C][C]13[/C][C]0.084967[/C][C]0.849673[/C][C]0.016993[/C][/ROW]
[ROW][C][115,120[[/C][C]117.5[/C][C]0[/C][C]0[/C][C]0.849673[/C][C]0[/C][/ROW]
[ROW][C][120,125[[/C][C]122.5[/C][C]21[/C][C]0.137255[/C][C]0.986928[/C][C]0.027451[/C][/ROW]
[ROW][C][125,130[[/C][C]127.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][130,135[[/C][C]132.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][135,140[[/C][C]137.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][140,145[[/C][C]142.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][145,150[[/C][C]147.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][150,155[[/C][C]152.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][155,160[[/C][C]157.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][160,165[[/C][C]162.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][165,170[[/C][C]167.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][170,175[[/C][C]172.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][175,180[[/C][C]177.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][180,185[[/C][C]182.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][185,190[[/C][C]187.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][190,195[[/C][C]192.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][195,200[[/C][C]197.5[/C][C]0[/C][C]0[/C][C]0.986928[/C][C]0[/C][/ROW]
[ROW][C][200,205[[/C][C]202.5[/C][C]1[/C][C]0.006536[/C][C]0.993464[/C][C]0.001307[/C][/ROW]
[ROW][C][205,210][/C][C]207.5[/C][C]1[/C][C]0.006536[/C][C]1[/C][C]0.001307[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211745&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211745&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[80,85[82.5140.0915030.0915030.018301
[85,90[87.5220.1437910.2352940.028758
[90,95[92.5660.4313730.6666670.086275
[95,100[97.5000.6666670
[100,105[102.5150.0980390.7647060.019608
[105,110[107.5000.7647060
[110,115[112.5130.0849670.8496730.016993
[115,120[117.5000.8496730
[120,125[122.5210.1372550.9869280.027451
[125,130[127.5000.9869280
[130,135[132.5000.9869280
[135,140[137.5000.9869280
[140,145[142.5000.9869280
[145,150[147.5000.9869280
[150,155[152.5000.9869280
[155,160[157.5000.9869280
[160,165[162.5000.9869280
[165,170[167.5000.9869280
[170,175[172.5000.9869280
[175,180[177.5000.9869280
[180,185[182.5000.9869280
[185,190[187.5000.9869280
[190,195[192.5000.9869280
[195,200[197.5000.9869280
[200,205[202.510.0065360.9934640.001307
[205,210]207.510.00653610.001307


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = no ; par3 = 512 ;
Parameters (R input):
par1 = 20 ; 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')
}