Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationWed, 05 Oct 2011 15:57:19 -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/2011/Oct/05/t13178447687eph9lx9t8y4zun.htm/, Retrieved Thu, 31 Oct 2024 22:53:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=126766, Retrieved Thu, 31 Oct 2024 22:53:03 +0000
QR Codes:

Original text written by user:Juist frequentietabel (histogram)
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W1
Estimated Impact114
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2011-10-05 19:57:19] [0701895f02f0ec4be946c800149e4a30] [Current]
- R P     [Histogram] [] [2011-10-05 20:09:25] [ae173f2c418793b42371cf566dac875a]
- R P     [Histogram] [] [2011-10-05 20:20:31] [ae173f2c418793b42371cf566dac875a]
- R       [Histogram] [] [2011-10-05 20:24:57] [ae173f2c418793b42371cf566dac875a]
- RM      [Kernel Density Estimation] [] [2011-10-05 20:38:34] [ae173f2c418793b42371cf566dac875a]
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Dataseries X:
24930
25115
25185
25335
25225
25625
25550
25090
25215
25305
25405
25440
25590
25270
24895
24985
24880
25055
25040
24940
25045
25635
25690
25625
24750
25115
25030
25095
25280
25620
25960
26280
26185
26135
26375
26465
26280
25910
26015
26295
26430
26610
26795
26800
26860
26745
26510
26635
26060
26095
25880
26145
26405
26390
26575
26255
26205
26360
26390
26360
26500
26485
26500
26620
26965
27200
27745
27750
27470
27185
27325
27385
27420
26955
27180
27375
27550
27495
27895
27760
28435
28405
28380
28630
28960
29050
29645
30210
29355
30610
31380
32120
31535
31960
30810
30320
31365
31635
31755
31435
31740
32155
32080
31975
31720
32580
33740
33185
32520
32390
32360
32180
32335
32015
32270
32630
32350
32520
32260
32550
32640
32585
32550
32445
31125
31030
30945
30350
30535
30330
30850
30850
30669
30520
29865
29555
29320
30500
29770
29800
29670
29335
28665
28890
28840
29010
28695
29115
29150
29135
29200
29235
29480
30050
30450
30675
30590
30515
30790
31005
31090
31200
31355
31405
30500
31250
31305
31480
31265
31355
31170
31445
31920
31665
31545
31200
31380
31495
31255
31360
31420
31290
31120
31160
31165
31045
30830
30925
30960
30725
30940
30910
31230
31310
30770
31080
31295
31230
31550
31420
31510
31560
31190
30845
30485
30790
30800
31025
30835
31110
31270
31090
30755
31460
32135
32680
32700
32515
32275
32200
31835
31985
31875
31795
32260
33255
33160
32195
33130
33950
34210
33855
33735
34175
34265
33915
33660
33720
33810
33590
33545
33660
33165
33800
33880
33975
33930
33905
33890
33640
34395
34245
33940





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=126766&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=126766&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=126766&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 time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[24000,25000[2450060.0237150.0237152.4e-05
[25000,26000[25500270.1067190.1304350.000107
[26000,27000[26500330.1304350.260870.00013
[27000,28000[27500140.0553360.3162065.5e-05
[28000,29000[2850090.0355730.3517793.6e-05
[29000,30000[29500170.0671940.4189726.7e-05
[30000,31000[30500330.1304350.5494070.00013
[31000,32000[31500570.2252960.7747040.000225
[32000,33000[32500280.1106720.8853750.000111
[33000,34000[33500240.0948620.9802379.5e-05
[34000,35000]3450050.01976312e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[24000,25000[ & 24500 & 6 & 0.023715 & 0.023715 & 2.4e-05 \tabularnewline
[25000,26000[ & 25500 & 27 & 0.106719 & 0.130435 & 0.000107 \tabularnewline
[26000,27000[ & 26500 & 33 & 0.130435 & 0.26087 & 0.00013 \tabularnewline
[27000,28000[ & 27500 & 14 & 0.055336 & 0.316206 & 5.5e-05 \tabularnewline
[28000,29000[ & 28500 & 9 & 0.035573 & 0.351779 & 3.6e-05 \tabularnewline
[29000,30000[ & 29500 & 17 & 0.067194 & 0.418972 & 6.7e-05 \tabularnewline
[30000,31000[ & 30500 & 33 & 0.130435 & 0.549407 & 0.00013 \tabularnewline
[31000,32000[ & 31500 & 57 & 0.225296 & 0.774704 & 0.000225 \tabularnewline
[32000,33000[ & 32500 & 28 & 0.110672 & 0.885375 & 0.000111 \tabularnewline
[33000,34000[ & 33500 & 24 & 0.094862 & 0.980237 & 9.5e-05 \tabularnewline
[34000,35000] & 34500 & 5 & 0.019763 & 1 & 2e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=126766&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][24000,25000[[/C][C]24500[/C][C]6[/C][C]0.023715[/C][C]0.023715[/C][C]2.4e-05[/C][/ROW]
[ROW][C][25000,26000[[/C][C]25500[/C][C]27[/C][C]0.106719[/C][C]0.130435[/C][C]0.000107[/C][/ROW]
[ROW][C][26000,27000[[/C][C]26500[/C][C]33[/C][C]0.130435[/C][C]0.26087[/C][C]0.00013[/C][/ROW]
[ROW][C][27000,28000[[/C][C]27500[/C][C]14[/C][C]0.055336[/C][C]0.316206[/C][C]5.5e-05[/C][/ROW]
[ROW][C][28000,29000[[/C][C]28500[/C][C]9[/C][C]0.035573[/C][C]0.351779[/C][C]3.6e-05[/C][/ROW]
[ROW][C][29000,30000[[/C][C]29500[/C][C]17[/C][C]0.067194[/C][C]0.418972[/C][C]6.7e-05[/C][/ROW]
[ROW][C][30000,31000[[/C][C]30500[/C][C]33[/C][C]0.130435[/C][C]0.549407[/C][C]0.00013[/C][/ROW]
[ROW][C][31000,32000[[/C][C]31500[/C][C]57[/C][C]0.225296[/C][C]0.774704[/C][C]0.000225[/C][/ROW]
[ROW][C][32000,33000[[/C][C]32500[/C][C]28[/C][C]0.110672[/C][C]0.885375[/C][C]0.000111[/C][/ROW]
[ROW][C][33000,34000[[/C][C]33500[/C][C]24[/C][C]0.094862[/C][C]0.980237[/C][C]9.5e-05[/C][/ROW]
[ROW][C][34000,35000][/C][C]34500[/C][C]5[/C][C]0.019763[/C][C]1[/C][C]2e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=126766&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=126766&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
[24000,25000[2450060.0237150.0237152.4e-05
[25000,26000[25500270.1067190.1304350.000107
[26000,27000[26500330.1304350.260870.00013
[27000,28000[27500140.0553360.3162065.5e-05
[28000,29000[2850090.0355730.3517793.6e-05
[29000,30000[29500170.0671940.4189726.7e-05
[30000,31000[30500330.1304350.5494070.00013
[31000,32000[31500570.2252960.7747040.000225
[32000,33000[32500280.1106720.8853750.000111
[33000,34000[33500240.0948620.9802379.5e-05
[34000,35000]3450050.01976312e-05



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')
}