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Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 01 Mar 2016 15:53:45 +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/2016/Mar/01/t14568476866r46baljwjjmiyc.htm/, Retrieved Tue, 07 May 2024 22:40:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=293167, Retrieved Tue, 07 May 2024 22:40:10 +0000
QR Codes:

Original text written by user:standaard aantal klassen
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Maximumprijs Bios...] [2016-03-01 15:27:06] [74be16979710d4c4e7c6647856088456]
- RMPD    [Histogram] [Vers Fruit - Hist...] [2016-03-01 15:53:45] [9229f16b23a3f07f1433c1291c3e5666] [Current]
- RMPD      [Kernel Density Estimation] [Vers Fruit - dich...] [2016-03-01 16:04:54] [b1a7cb6d93e9c32863cdeb6d14632a38]
- RMPD      [Quartiles] [Maximumprijs Bios...] [2016-03-01 16:13:37] [b1a7cb6d93e9c32863cdeb6d14632a38]
- RMPD      [Notched Boxplots] [Maximumprijs Bios...] [2016-03-01 16:17:28] [b1a7cb6d93e9c32863cdeb6d14632a38]
- RMPD      [Quartiles] [Vers Fruit - Kwar...] [2016-03-01 16:27:24] [b1a7cb6d93e9c32863cdeb6d14632a38]
- RMP       [Quartiles] [Vers Fruit - Kwar...] [2016-03-01 16:32:44] [b1a7cb6d93e9c32863cdeb6d14632a38]
- RMP       [Notched Boxplots] [Vers Fruit - Box ...] [2016-03-01 16:36:29] [b1a7cb6d93e9c32863cdeb6d14632a38]
- RMPD      [Harrell-Davis Quantiles] [Levengeborenen va...] [2016-03-01 16:46:24] [74be16979710d4c4e7c6647856088456]
- RMPD      [Harrell-Davis Quantiles] [Levengeborenen va...] [2016-03-01 16:46:24] [b1a7cb6d93e9c32863cdeb6d14632a38]
- R           [Harrell-Davis Quantiles] [Levengeborenen va...] [2016-03-01 16:53:03] [b1a7cb6d93e9c32863cdeb6d14632a38]
- R  D        [Harrell-Davis Quantiles] [Vers Fruit - Deci...] [2016-03-01 17:04:58] [b1a7cb6d93e9c32863cdeb6d14632a38]
- R  D        [Harrell-Davis Quantiles] [Vers Fruit - Perc...] [2016-03-01 17:10:40] [b1a7cb6d93e9c32863cdeb6d14632a38]
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Dataseries X:
82,6
85,99
86,85
86,12
97,19
89,8
90,27
90,68
90,05
90,28
91,52
88,3
85,31
87,86
87,77
88,44
88,73
94,4
94,09
90,32
89,68
94,15
95,2
91,82
90,33
95,14
96,06
97,21
100,33
98,79
102,48
99,29
98,83
97,25
94,55
93,53
93,58
95,79
94,77
94,2
96,23
92,3
88,86
86,44
86,21
88,57
90,69
89
86,88
90,65
90,68
89,64
102,62
101,84
92,51
94,29
94,68
96,94
94,03
89,65
84,9
89,07
89,8
93,22
92,23
98,41
96,63
89,8
90
92,13
93,27
90,81
85,42
88,28
88,73
90,18
92,74
96,13
94,85
94,25
96,94
101,22
98,71
95,51
93,91
98,17
97,59
99,64
107,88
108,49
100,25
99,27
101,73
101,25
97,09
94,74
94,53
93,48
96,05
106,22
98,33
99,86
93,78
88,96
83,77
89,46
86,78
88,4
87,19
92,23
95,99
104,75
105,63
108,71
96,4
93,31
93,77
98,7
95,04
95,61




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293167&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293167&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293167&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'Gwilym Jenkins' @ jenkins.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[80,85[82.530.0250.0250.005
[85,90[87.5300.250.2750.05
[90,95[92.5420.350.6250.07
[95,100[97.5310.2583330.8833330.051667
[100,105[102.590.0750.9583330.015
[105,110]107.550.04166710.008333

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[80,85[ & 82.5 & 3 & 0.025 & 0.025 & 0.005 \tabularnewline
[85,90[ & 87.5 & 30 & 0.25 & 0.275 & 0.05 \tabularnewline
[90,95[ & 92.5 & 42 & 0.35 & 0.625 & 0.07 \tabularnewline
[95,100[ & 97.5 & 31 & 0.258333 & 0.883333 & 0.051667 \tabularnewline
[100,105[ & 102.5 & 9 & 0.075 & 0.958333 & 0.015 \tabularnewline
[105,110] & 107.5 & 5 & 0.041667 & 1 & 0.008333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293167&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][80,85[[/C][C]82.5[/C][C]3[/C][C]0.025[/C][C]0.025[/C][C]0.005[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]30[/C][C]0.25[/C][C]0.275[/C][C]0.05[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]42[/C][C]0.35[/C][C]0.625[/C][C]0.07[/C][/ROW]
[ROW][C][95,100[[/C][C]97.5[/C][C]31[/C][C]0.258333[/C][C]0.883333[/C][C]0.051667[/C][/ROW]
[ROW][C][100,105[[/C][C]102.5[/C][C]9[/C][C]0.075[/C][C]0.958333[/C][C]0.015[/C][/ROW]
[ROW][C][105,110][/C][C]107.5[/C][C]5[/C][C]0.041667[/C][C]1[/C][C]0.008333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293167&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293167&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
[80,85[82.530.0250.0250.005
[85,90[87.5300.250.2750.05
[90,95[92.5420.350.6250.07
[95,100[97.5310.2583330.8833330.051667
[100,105[102.590.0750.9583330.015
[105,110]107.550.04166710.008333



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 {
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')
}