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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 computationMon, 20 Dec 2010 15:10:31 +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/2010/Dec/20/t1292857691dnpmm7xpfc3mges.htm/, Retrieved Fri, 03 May 2024 19:24:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112989, Retrieved Fri, 03 May 2024 19:24:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [histogram] [2010-11-24 10:12:12] [dcd1a35a8985187cb1e9de87792355b2]
F       [Histogram] [] [2010-11-26 12:37:32] [897115520fe7b6114489bc0eeed64548]
-    D    [Histogram] [] [2010-11-26 15:14:54] [bfba28641a1925a39268a5d6ad3b00f2]
-           [Histogram] [] [2010-11-26 20:08:03] [f9d37301ea08122b4d103fe011f2b292]
-    D          [Histogram] [] [2010-12-20 15:10:31] [a90f4492977f0c16b1e3c8673c334a45] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
313737
312276
309391
302950
300316
304035
333476
337698
335932
323931
313927
314485
313218
309664
302963
298989
298423
301631
329765
335083
327616
309119
295916
291413
291542
284678
276475
272566
264981
263290
296806
303598
286994
276427
266424
267153
268381
262522
255542
253158
243803
250741
280445
285257
270976
261076
255603
260376
263903
264291
263276
262572
256167
264221
293860
300713
287224
275902
271115
277509
279681

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112989&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112989&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112989&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[240000,250000[24500010.0163930.0163932e-06
[250000,260000[25500050.0819670.0983618e-06
[260000,270000[265000130.2131150.3114752.1e-05
[270000,280000[27500080.1311480.4426231.3e-05
[280000,290000[28500050.0819670.524598e-06
[290000,3e+05[29500070.1147540.6393441.1e-05
[3e+05,310000[305000100.1639340.8032791.6e-05
[310000,320000[31500050.0819670.8852468e-06
[320000,330000[32500030.049180.9344265e-06
[330000,340000]33500040.06557417e-06

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[240000,250000[ & 245000 & 1 & 0.016393 & 0.016393 & 2e-06 \tabularnewline
[250000,260000[ & 255000 & 5 & 0.081967 & 0.098361 & 8e-06 \tabularnewline
[260000,270000[ & 265000 & 13 & 0.213115 & 0.311475 & 2.1e-05 \tabularnewline
[270000,280000[ & 275000 & 8 & 0.131148 & 0.442623 & 1.3e-05 \tabularnewline
[280000,290000[ & 285000 & 5 & 0.081967 & 0.52459 & 8e-06 \tabularnewline
[290000,3e+05[ & 295000 & 7 & 0.114754 & 0.639344 & 1.1e-05 \tabularnewline
[3e+05,310000[ & 305000 & 10 & 0.163934 & 0.803279 & 1.6e-05 \tabularnewline
[310000,320000[ & 315000 & 5 & 0.081967 & 0.885246 & 8e-06 \tabularnewline
[320000,330000[ & 325000 & 3 & 0.04918 & 0.934426 & 5e-06 \tabularnewline
[330000,340000] & 335000 & 4 & 0.065574 & 1 & 7e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112989&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][240000,250000[[/C][C]245000[/C][C]1[/C][C]0.016393[/C][C]0.016393[/C][C]2e-06[/C][/ROW]
[ROW][C][250000,260000[[/C][C]255000[/C][C]5[/C][C]0.081967[/C][C]0.098361[/C][C]8e-06[/C][/ROW]
[ROW][C][260000,270000[[/C][C]265000[/C][C]13[/C][C]0.213115[/C][C]0.311475[/C][C]2.1e-05[/C][/ROW]
[ROW][C][270000,280000[[/C][C]275000[/C][C]8[/C][C]0.131148[/C][C]0.442623[/C][C]1.3e-05[/C][/ROW]
[ROW][C][280000,290000[[/C][C]285000[/C][C]5[/C][C]0.081967[/C][C]0.52459[/C][C]8e-06[/C][/ROW]
[ROW][C][290000,3e+05[[/C][C]295000[/C][C]7[/C][C]0.114754[/C][C]0.639344[/C][C]1.1e-05[/C][/ROW]
[ROW][C][3e+05,310000[[/C][C]305000[/C][C]10[/C][C]0.163934[/C][C]0.803279[/C][C]1.6e-05[/C][/ROW]
[ROW][C][310000,320000[[/C][C]315000[/C][C]5[/C][C]0.081967[/C][C]0.885246[/C][C]8e-06[/C][/ROW]
[ROW][C][320000,330000[[/C][C]325000[/C][C]3[/C][C]0.04918[/C][C]0.934426[/C][C]5e-06[/C][/ROW]
[ROW][C][330000,340000][/C][C]335000[/C][C]4[/C][C]0.065574[/C][C]1[/C][C]7e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112989&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112989&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
[240000,250000[24500010.0163930.0163932e-06
[250000,260000[25500050.0819670.0983618e-06
[260000,270000[265000130.2131150.3114752.1e-05
[270000,280000[27500080.1311480.4426231.3e-05
[280000,290000[28500050.0819670.524598e-06
[290000,3e+05[29500070.1147540.6393441.1e-05
[3e+05,310000[305000100.1639340.8032791.6e-05
[310000,320000[31500050.0819670.8852468e-06
[320000,330000[32500030.049180.9344265e-06
[330000,340000]33500040.06557417e-06


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):
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')
}