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Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 30 Nov 2015 21:44:38 +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/2015/Nov/30/t1448919921h8ty4rt4w4nwqw3.htm/, Retrieved Tue, 14 May 2024 02:46:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284639, Retrieved Tue, 14 May 2024 02:46:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [studio 100 maximu...] [2015-10-01 20:05:23] [1625b1453ed47b256ce4b6eedb089cd5]
- RMPD    [Histogram] [verbetering kaas ...] [2015-11-30 21:44:38] [c4e632f9a17048eeb9519d4e8ae83546] [Current]
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Dataseries X:
79.58
80.08
80.41
80.34
80.32
80.39
81.01
81.54
82.48
84.68
88.26
90.6
92.46
93.31
93.58
93.92
93.92
93.67
93.76
93.95
93.89
94.07
93.93
93.35
93.58
93.55
93.44
93.38
93.17
92.95
93.37
94.13
94.07
94
94.47
94.81
94.18
94.14
93.96
93.23
93.13
92.51
92.49
92.73
92.75
92.83
92.85
93.27
93.98
94.34
94.57
94.62
94.82
95.07
95.72
96.06
96.54
96.38
96.8
97.02
97.29
97.45
97.95
97.69
97.63
97.35
97.38
98.06
98.34
98.53
98.79
98.77
99.2
99.76
99.84
99.83
99.88
99.48
99.66
99.58
99.89
100.7
101.19
100.99
101.52
101.75
101.56
102.57
102.66
102.62
102.76
102.73
102.26
101.72
101.48
100.93




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284639&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284639&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284639&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'Gertrude Mary Cox' @ cox.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[79,80[79.510.0104170.0104170.010417
[80,81[80.550.0520830.06250.052083
[81,82[81.520.0208330.0833330.020833
[82,83[82.510.0104170.093750.010417
[83,84[83.5000.093750
[84,85[84.510.0104170.1041670.010417
[85,86[85.5000.1041670
[86,87[86.5000.1041670
[87,88[87.5000.1041670
[88,89[88.510.0104170.1145830.010417
[89,90[89.5000.1145830
[90,91[90.510.0104170.1250.010417
[91,92[91.5000.1250
[92,93[92.580.0833330.2083330.083333
[93,94[93.5210.218750.4270830.21875
[94,95[94.5120.1250.5520830.125
[95,96[95.520.0208330.5729170.020833
[96,97[96.540.0416670.6145830.041667
[97,98[97.580.0833330.6979170.083333
[98,99[98.550.0520830.750.052083
[99,100[99.590.093750.843750.09375
[100,101[100.530.031250.8750.03125
[101,102[101.560.06250.93750.0625
[102,103]102.560.062510.0625

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[79,80[ & 79.5 & 1 & 0.010417 & 0.010417 & 0.010417 \tabularnewline
[80,81[ & 80.5 & 5 & 0.052083 & 0.0625 & 0.052083 \tabularnewline
[81,82[ & 81.5 & 2 & 0.020833 & 0.083333 & 0.020833 \tabularnewline
[82,83[ & 82.5 & 1 & 0.010417 & 0.09375 & 0.010417 \tabularnewline
[83,84[ & 83.5 & 0 & 0 & 0.09375 & 0 \tabularnewline
[84,85[ & 84.5 & 1 & 0.010417 & 0.104167 & 0.010417 \tabularnewline
[85,86[ & 85.5 & 0 & 0 & 0.104167 & 0 \tabularnewline
[86,87[ & 86.5 & 0 & 0 & 0.104167 & 0 \tabularnewline
[87,88[ & 87.5 & 0 & 0 & 0.104167 & 0 \tabularnewline
[88,89[ & 88.5 & 1 & 0.010417 & 0.114583 & 0.010417 \tabularnewline
[89,90[ & 89.5 & 0 & 0 & 0.114583 & 0 \tabularnewline
[90,91[ & 90.5 & 1 & 0.010417 & 0.125 & 0.010417 \tabularnewline
[91,92[ & 91.5 & 0 & 0 & 0.125 & 0 \tabularnewline
[92,93[ & 92.5 & 8 & 0.083333 & 0.208333 & 0.083333 \tabularnewline
[93,94[ & 93.5 & 21 & 0.21875 & 0.427083 & 0.21875 \tabularnewline
[94,95[ & 94.5 & 12 & 0.125 & 0.552083 & 0.125 \tabularnewline
[95,96[ & 95.5 & 2 & 0.020833 & 0.572917 & 0.020833 \tabularnewline
[96,97[ & 96.5 & 4 & 0.041667 & 0.614583 & 0.041667 \tabularnewline
[97,98[ & 97.5 & 8 & 0.083333 & 0.697917 & 0.083333 \tabularnewline
[98,99[ & 98.5 & 5 & 0.052083 & 0.75 & 0.052083 \tabularnewline
[99,100[ & 99.5 & 9 & 0.09375 & 0.84375 & 0.09375 \tabularnewline
[100,101[ & 100.5 & 3 & 0.03125 & 0.875 & 0.03125 \tabularnewline
[101,102[ & 101.5 & 6 & 0.0625 & 0.9375 & 0.0625 \tabularnewline
[102,103] & 102.5 & 6 & 0.0625 & 1 & 0.0625 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284639&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][79,80[[/C][C]79.5[/C][C]1[/C][C]0.010417[/C][C]0.010417[/C][C]0.010417[/C][/ROW]
[ROW][C][80,81[[/C][C]80.5[/C][C]5[/C][C]0.052083[/C][C]0.0625[/C][C]0.052083[/C][/ROW]
[ROW][C][81,82[[/C][C]81.5[/C][C]2[/C][C]0.020833[/C][C]0.083333[/C][C]0.020833[/C][/ROW]
[ROW][C][82,83[[/C][C]82.5[/C][C]1[/C][C]0.010417[/C][C]0.09375[/C][C]0.010417[/C][/ROW]
[ROW][C][83,84[[/C][C]83.5[/C][C]0[/C][C]0[/C][C]0.09375[/C][C]0[/C][/ROW]
[ROW][C][84,85[[/C][C]84.5[/C][C]1[/C][C]0.010417[/C][C]0.104167[/C][C]0.010417[/C][/ROW]
[ROW][C][85,86[[/C][C]85.5[/C][C]0[/C][C]0[/C][C]0.104167[/C][C]0[/C][/ROW]
[ROW][C][86,87[[/C][C]86.5[/C][C]0[/C][C]0[/C][C]0.104167[/C][C]0[/C][/ROW]
[ROW][C][87,88[[/C][C]87.5[/C][C]0[/C][C]0[/C][C]0.104167[/C][C]0[/C][/ROW]
[ROW][C][88,89[[/C][C]88.5[/C][C]1[/C][C]0.010417[/C][C]0.114583[/C][C]0.010417[/C][/ROW]
[ROW][C][89,90[[/C][C]89.5[/C][C]0[/C][C]0[/C][C]0.114583[/C][C]0[/C][/ROW]
[ROW][C][90,91[[/C][C]90.5[/C][C]1[/C][C]0.010417[/C][C]0.125[/C][C]0.010417[/C][/ROW]
[ROW][C][91,92[[/C][C]91.5[/C][C]0[/C][C]0[/C][C]0.125[/C][C]0[/C][/ROW]
[ROW][C][92,93[[/C][C]92.5[/C][C]8[/C][C]0.083333[/C][C]0.208333[/C][C]0.083333[/C][/ROW]
[ROW][C][93,94[[/C][C]93.5[/C][C]21[/C][C]0.21875[/C][C]0.427083[/C][C]0.21875[/C][/ROW]
[ROW][C][94,95[[/C][C]94.5[/C][C]12[/C][C]0.125[/C][C]0.552083[/C][C]0.125[/C][/ROW]
[ROW][C][95,96[[/C][C]95.5[/C][C]2[/C][C]0.020833[/C][C]0.572917[/C][C]0.020833[/C][/ROW]
[ROW][C][96,97[[/C][C]96.5[/C][C]4[/C][C]0.041667[/C][C]0.614583[/C][C]0.041667[/C][/ROW]
[ROW][C][97,98[[/C][C]97.5[/C][C]8[/C][C]0.083333[/C][C]0.697917[/C][C]0.083333[/C][/ROW]
[ROW][C][98,99[[/C][C]98.5[/C][C]5[/C][C]0.052083[/C][C]0.75[/C][C]0.052083[/C][/ROW]
[ROW][C][99,100[[/C][C]99.5[/C][C]9[/C][C]0.09375[/C][C]0.84375[/C][C]0.09375[/C][/ROW]
[ROW][C][100,101[[/C][C]100.5[/C][C]3[/C][C]0.03125[/C][C]0.875[/C][C]0.03125[/C][/ROW]
[ROW][C][101,102[[/C][C]101.5[/C][C]6[/C][C]0.0625[/C][C]0.9375[/C][C]0.0625[/C][/ROW]
[ROW][C][102,103][/C][C]102.5[/C][C]6[/C][C]0.0625[/C][C]1[/C][C]0.0625[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284639&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284639&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
[79,80[79.510.0104170.0104170.010417
[80,81[80.550.0520830.06250.052083
[81,82[81.520.0208330.0833330.020833
[82,83[82.510.0104170.093750.010417
[83,84[83.5000.093750
[84,85[84.510.0104170.1041670.010417
[85,86[85.5000.1041670
[86,87[86.5000.1041670
[87,88[87.5000.1041670
[88,89[88.510.0104170.1145830.010417
[89,90[89.5000.1145830
[90,91[90.510.0104170.1250.010417
[91,92[91.5000.1250
[92,93[92.580.0833330.2083330.083333
[93,94[93.5210.218750.4270830.21875
[94,95[94.5120.1250.5520830.125
[95,96[95.520.0208330.5729170.020833
[96,97[96.540.0416670.6145830.041667
[97,98[97.580.0833330.6979170.083333
[98,99[98.550.0520830.750.052083
[99,100[99.590.093750.843750.09375
[100,101[100.530.031250.8750.03125
[101,102[101.560.06250.93750.0625
[102,103]102.560.062510.0625



Parameters (Session):
par1 = 24 ; par2 = yellow ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 24 ; par2 = yellow ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '24'
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')
}