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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 computationFri, 23 Dec 2016 10:27:09 +0100
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/Dec/23/t14824852787uh6wa2al3rom5o.htm/, Retrieved Fri, 01 Nov 2024 03:37:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302809, Retrieved Fri, 01 Nov 2024 03:37:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [histogram en freq...] [2016-12-23 09:27:09] [bd7223969ac5b08f41438741a34686d6] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4981,8
4938
4915,6
4938,4
4977,6
5045
5034,8
5094,8
5128,8
5181,8
5232
5384,4
5340,4
5452,6
5541,2
5627,2
5712
5794,2
5898,6
6021
6117,2
6245,4
6305,8
6327,2
6374,2
6383,2
6380
6373,4
6385
6399
6374,6
6342
6287,8
6198,8
6113,6
6110
6059
6004,6
5989,6
5988
5963
5972,2
5962,2
5930,4
5901,2
5860,8
5804,8
5727,6
5744,2
5744,8
5763,8
5774,6
5797,6
5806,8
5806,2
5809
5845,6
5876,8
5925,8
5972,2
5955,2
5972,4
5979,6
5976,4
5990,4
6029,4
6046,2
6094,6
6114,6
6149,4
6266,2
6312
6338
6417
6392,6
6455,4
6445,2
6415
6490,8
6552,8
6522,8
6568,8
6586,2
6627,6
6643,2
6635,4
6628,2
6628,8
6623,4
6596
6625
6613
6608,2
6590,2
6602,8
6525
6487,6
6449
6461,8
6476,8
6436,8
6399,4
6411,2
6356
6356,8
6337
6334,6
6310,6
6320,8
6321,8
6305,8
6293,8
6281,4
6306,8
6281,2
6325,8

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302809&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=302809&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302809&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[4800,5000[490050.0431030.0431030.000216
[5000,5200[510050.0431030.0862070.000216
[5200,5400[530030.0258620.1120690.000129
[5400,5600[550020.0172410.129318.6e-05
[5600,5800[570090.0775860.2068970.000388
[5800,6000[5900220.1896550.3965520.000948
[6000,6200[6100120.1034480.50.000517
[6200,6400[6300300.2586210.7586210.001293
[6400,6600[6500180.1551720.9137930.000776
[6600,6800]6700100.08620710.000431

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[4800,5000[ & 4900 & 5 & 0.043103 & 0.043103 & 0.000216 \tabularnewline
[5000,5200[ & 5100 & 5 & 0.043103 & 0.086207 & 0.000216 \tabularnewline
[5200,5400[ & 5300 & 3 & 0.025862 & 0.112069 & 0.000129 \tabularnewline
[5400,5600[ & 5500 & 2 & 0.017241 & 0.12931 & 8.6e-05 \tabularnewline
[5600,5800[ & 5700 & 9 & 0.077586 & 0.206897 & 0.000388 \tabularnewline
[5800,6000[ & 5900 & 22 & 0.189655 & 0.396552 & 0.000948 \tabularnewline
[6000,6200[ & 6100 & 12 & 0.103448 & 0.5 & 0.000517 \tabularnewline
[6200,6400[ & 6300 & 30 & 0.258621 & 0.758621 & 0.001293 \tabularnewline
[6400,6600[ & 6500 & 18 & 0.155172 & 0.913793 & 0.000776 \tabularnewline
[6600,6800] & 6700 & 10 & 0.086207 & 1 & 0.000431 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302809&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][4800,5000[[/C][C]4900[/C][C]5[/C][C]0.043103[/C][C]0.043103[/C][C]0.000216[/C][/ROW]
[ROW][C][5000,5200[[/C][C]5100[/C][C]5[/C][C]0.043103[/C][C]0.086207[/C][C]0.000216[/C][/ROW]
[ROW][C][5200,5400[[/C][C]5300[/C][C]3[/C][C]0.025862[/C][C]0.112069[/C][C]0.000129[/C][/ROW]
[ROW][C][5400,5600[[/C][C]5500[/C][C]2[/C][C]0.017241[/C][C]0.12931[/C][C]8.6e-05[/C][/ROW]
[ROW][C][5600,5800[[/C][C]5700[/C][C]9[/C][C]0.077586[/C][C]0.206897[/C][C]0.000388[/C][/ROW]
[ROW][C][5800,6000[[/C][C]5900[/C][C]22[/C][C]0.189655[/C][C]0.396552[/C][C]0.000948[/C][/ROW]
[ROW][C][6000,6200[[/C][C]6100[/C][C]12[/C][C]0.103448[/C][C]0.5[/C][C]0.000517[/C][/ROW]
[ROW][C][6200,6400[[/C][C]6300[/C][C]30[/C][C]0.258621[/C][C]0.758621[/C][C]0.001293[/C][/ROW]
[ROW][C][6400,6600[[/C][C]6500[/C][C]18[/C][C]0.155172[/C][C]0.913793[/C][C]0.000776[/C][/ROW]
[ROW][C][6600,6800][/C][C]6700[/C][C]10[/C][C]0.086207[/C][C]1[/C][C]0.000431[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302809&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302809&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
[4800,5000[490050.0431030.0431030.000216
[5000,5200[510050.0431030.0862070.000216
[5200,5400[530030.0258620.1120690.000129
[5400,5600[550020.0172410.129318.6e-05
[5600,5800[570090.0775860.2068970.000388
[5800,6000[5900220.1896550.3965520.000948
[6000,6200[6100120.1034480.50.000517
[6200,6400[6300300.2586210.7586210.001293
[6400,6600[6500180.1551720.9137930.000776
[6600,6800]6700100.08620710.000431


Figures (Output of Computation)

Input Parameters & R Code

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):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
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,'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')
}