Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationWed, 21 Dec 2011 12:23:23 -0500
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/Dec/21/t1324488291040pcqsblobk26n.htm/, Retrieved Sun, 10 Nov 2024 19:44:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=158901, Retrieved Sun, 10 Nov 2024 19:44:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [Classical Decomposition] [ws8. additional] [2011-11-30 13:03:24] [8ae0a4da1b3ee81f40dbba5e42914d07]
- RMP           [Exponential Smoothing] [WS8 Monthly birth...] [2011-11-30 14:31:27] [2628f630b839c9d14ba9c3627ab0414a]
- RMPD              [Histogram] [paper] [2011-12-21 17:23:23] [3d1c016f2f3d502d2cccf121bc4326eb] [Current]
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Dataseries X:
-31.0980235042716
-59.8206924271108
-83.5404637229203
-76.6837390525943
-55.7725703639553
-29.62380040276
-403.243804757836
-416.782395531722
-213.421552958589
371.566721695855
165.983275906532
542.6202623301
295.02721709437
-21.1190278168924
437.4008577275
365.294800512585
67.9306326630958
-247.788856282479
545.098074661517
-296.773620935714
352.477617436036
283.798200110577
-273.315875572704
446.06222457008
-214.72781956204
-60.4206198854663
372.155927347334
99.2591381678085
318.424339918272
125.277834109822
-327.853683550757
-432.970794551573
442.139159285423
14.3549856459813
299.040533753827
88.2365194871691
-180.537099245963
201.985172786433
193.536881410406
-313.092895033498
-152.748572628851
299.982624154345
42.4811421719933
133.842278481663
-129.830065090609
-699.373730899397
171.563382431515
-24.5384434740972
116.363164839684
-218.154308468131
-257.102541429251
98.6124781717281
-190.742241794984
198.422707475118
-145.26733998686
611.517071444689
56.0522598394018
-117.514342950461
-3.71499521678197
296.99038945692
360.610007278467
61.6319235909414
-746.579530943922




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158901&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158901&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158901&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'AstonUniversity' @ aston.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[-800,-600[-70020.0317460.0317460.000159
[-600,-400[-50030.0476190.0793650.000238
[-400,-200[-30090.1428570.2222220.000714
[-200,0[-100160.2539680.476190.00127
[0,200[100150.2380950.7142860.00119
[200,400[300120.1904760.9047620.000952
[400,600[50050.0793650.9841270.000397
[600,800]70010.01587317.9e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[-800,-600[ & -700 & 2 & 0.031746 & 0.031746 & 0.000159 \tabularnewline
[-600,-400[ & -500 & 3 & 0.047619 & 0.079365 & 0.000238 \tabularnewline
[-400,-200[ & -300 & 9 & 0.142857 & 0.222222 & 0.000714 \tabularnewline
[-200,0[ & -100 & 16 & 0.253968 & 0.47619 & 0.00127 \tabularnewline
[0,200[ & 100 & 15 & 0.238095 & 0.714286 & 0.00119 \tabularnewline
[200,400[ & 300 & 12 & 0.190476 & 0.904762 & 0.000952 \tabularnewline
[400,600[ & 500 & 5 & 0.079365 & 0.984127 & 0.000397 \tabularnewline
[600,800] & 700 & 1 & 0.015873 & 1 & 7.9e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158901&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][-800,-600[[/C][C]-700[/C][C]2[/C][C]0.031746[/C][C]0.031746[/C][C]0.000159[/C][/ROW]
[ROW][C][-600,-400[[/C][C]-500[/C][C]3[/C][C]0.047619[/C][C]0.079365[/C][C]0.000238[/C][/ROW]
[ROW][C][-400,-200[[/C][C]-300[/C][C]9[/C][C]0.142857[/C][C]0.222222[/C][C]0.000714[/C][/ROW]
[ROW][C][-200,0[[/C][C]-100[/C][C]16[/C][C]0.253968[/C][C]0.47619[/C][C]0.00127[/C][/ROW]
[ROW][C][0,200[[/C][C]100[/C][C]15[/C][C]0.238095[/C][C]0.714286[/C][C]0.00119[/C][/ROW]
[ROW][C][200,400[[/C][C]300[/C][C]12[/C][C]0.190476[/C][C]0.904762[/C][C]0.000952[/C][/ROW]
[ROW][C][400,600[[/C][C]500[/C][C]5[/C][C]0.079365[/C][C]0.984127[/C][C]0.000397[/C][/ROW]
[ROW][C][600,800][/C][C]700[/C][C]1[/C][C]0.015873[/C][C]1[/C][C]7.9e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158901&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158901&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
[-800,-600[-70020.0317460.0317460.000159
[-600,-400[-50030.0476190.0793650.000238
[-400,-200[-30090.1428570.2222220.000714
[-200,0[-100160.2539680.476190.00127
[0,200[100150.2380950.7142860.00119
[200,400[300120.1904760.9047620.000952
[400,600[50050.0793650.9841270.000397
[600,800]70010.01587317.9e-05



Parameters (Session):
par1 = 12 ;
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')
}