Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationFri, 12 Aug 2016 11:31:52 +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/Aug/12/t1470997977269vhmaycl7db67.htm/, Retrieved Sun, 05 May 2024 15:00:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296419, Retrieved Sun, 05 May 2024 15:00:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Omzet Mentos Aardbei] [2016-07-17 11:11:37] [74be16979710d4c4e7c6647856088456]
-   P   [Univariate Data Series] [Omzet Mentos Aardbei] [2016-08-02 12:13:56] [74be16979710d4c4e7c6647856088456]
-   P     [Univariate Data Series] [] [2016-08-12 10:07:18] [74be16979710d4c4e7c6647856088456]
- R  D      [Univariate Data Series] [] [2016-08-12 10:23:50] [74be16979710d4c4e7c6647856088456]
- RMP           [Histogram] [] [2016-08-12 10:31:52] [d41d8cd98f00b204e9800998ecf8427e] [Current]
- RMP             [Kernel Density Estimation] [] [2016-08-12 11:05:45] [74be16979710d4c4e7c6647856088456]
- RMPD            [Quartiles] [] [2016-08-12 11:55:21] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
425.25
417.75
410.25
395.25
546.75
539.25
425.25
349.50
357.00
357.00
364.50
380.25
334.50
288.75
251.25
251.25
395.25
410.25
296.25
167.25
235.50
235.50
288.75
319.50
312.00
235.50
273.75
258.75
387.75
357.00
235.50
144.75
228.00
251.25
273.75
303.75
243.00
190.50
213.00
220.50
417.75
417.75
303.75
288.75
334.50
312.00
372.75
448.50
463.50
357.00
327.00
296.25
501.75
516.75
478.50
516.75
509.25
448.50
516.75
592.50
623.25
531.75
471.00
516.75
714.00
774.75
759.75
789.75
782.25
706.50
835.50
866.25
911.25
774.75
721.50
782.25
927.00
1056.00
1025.25
1025.25
1040.25
987.75
1124.25
1124.25
1101.00
972.00
995.25
1010.25
1109.25
1238.25
1146.75
1192.50
1154.25
1131.75
1306.50
1268.25
1215.00
1139.25
1215.00
1253.25
1299.00
1359.75
1299.00
1336.50
1290.75
1283.25
1473.00
1488.75
1428.00
1321.50
1412.25
1450.50
1496.25
1564.50
1496.25
1549.50
1526.25
1443.00
1617.75
1617.75




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

\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
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296419&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]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296419&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296419&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







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,200[10030.0250.0250.000125
[200,400[300380.3166670.3416670.001583
[400,600[500220.1833330.5250.000917
[600,800[700100.0833330.6083330.000417
[800,1000[90070.0583330.6666670.000292
[1000,1200[1100140.1166670.7833330.000583
[1200,1400[1300130.1083330.8916670.000542
[1400,1600[1500110.0916670.9833330.000458
[1600,1800]170020.01666718.3e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,200[ & 100 & 3 & 0.025 & 0.025 & 0.000125 \tabularnewline
[200,400[ & 300 & 38 & 0.316667 & 0.341667 & 0.001583 \tabularnewline
[400,600[ & 500 & 22 & 0.183333 & 0.525 & 0.000917 \tabularnewline
[600,800[ & 700 & 10 & 0.083333 & 0.608333 & 0.000417 \tabularnewline
[800,1000[ & 900 & 7 & 0.058333 & 0.666667 & 0.000292 \tabularnewline
[1000,1200[ & 1100 & 14 & 0.116667 & 0.783333 & 0.000583 \tabularnewline
[1200,1400[ & 1300 & 13 & 0.108333 & 0.891667 & 0.000542 \tabularnewline
[1400,1600[ & 1500 & 11 & 0.091667 & 0.983333 & 0.000458 \tabularnewline
[1600,1800] & 1700 & 2 & 0.016667 & 1 & 8.3e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296419&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][0,200[[/C][C]100[/C][C]3[/C][C]0.025[/C][C]0.025[/C][C]0.000125[/C][/ROW]
[ROW][C][200,400[[/C][C]300[/C][C]38[/C][C]0.316667[/C][C]0.341667[/C][C]0.001583[/C][/ROW]
[ROW][C][400,600[[/C][C]500[/C][C]22[/C][C]0.183333[/C][C]0.525[/C][C]0.000917[/C][/ROW]
[ROW][C][600,800[[/C][C]700[/C][C]10[/C][C]0.083333[/C][C]0.608333[/C][C]0.000417[/C][/ROW]
[ROW][C][800,1000[[/C][C]900[/C][C]7[/C][C]0.058333[/C][C]0.666667[/C][C]0.000292[/C][/ROW]
[ROW][C][1000,1200[[/C][C]1100[/C][C]14[/C][C]0.116667[/C][C]0.783333[/C][C]0.000583[/C][/ROW]
[ROW][C][1200,1400[[/C][C]1300[/C][C]13[/C][C]0.108333[/C][C]0.891667[/C][C]0.000542[/C][/ROW]
[ROW][C][1400,1600[[/C][C]1500[/C][C]11[/C][C]0.091667[/C][C]0.983333[/C][C]0.000458[/C][/ROW]
[ROW][C][1600,1800][/C][C]1700[/C][C]2[/C][C]0.016667[/C][C]1[/C][C]8.3e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296419&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296419&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
[0,200[10030.0250.0250.000125
[200,400[300380.3166670.3416670.001583
[400,600[500220.1833330.5250.000917
[600,800[700100.0833330.6083330.000417
[800,1000[90070.0583330.6666670.000292
[1000,1200[1100140.1166670.7833330.000583
[1200,1400[1300130.1083330.8916670.000542
[1400,1600[1500110.0916670.9833330.000458
[1600,1800]170020.01666718.3e-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):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '10'
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')
}