Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSat, 20 Feb 2016 14:51:22 +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/Feb/20/t14559799722di9zpy5df3ip83.htm/, Retrieved Thu, 09 May 2024 01:34:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=292313, Retrieved Thu, 09 May 2024 01:34:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [consumptieprijsin...] [2016-02-05 13:48:21] [37f2dab1f2148688a8d30ad5b541bb83]
- RMPD    [Histogram] [] [2016-02-20 14:51:22] [567a9be58124adae7ccc8a0c8709ba48] [Current]
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Dataseries X:
84.97
85.57
85.74
85.88
85.88
85.96
85.96
85.99
86.02
86.14
86.3
86.32
86.32
86.77
87.47
87.39
87.3
87.31
87.31
87.38
87.4
87.32
87.37
87.4
87.4
87.89
87.7
87.89
88.02
88.08
88.08
88.15
88.21
88.41
88.39
88.41
88.41
89.1
90.35
90.61
91.18
91.22
91.22
91.4
91.52
91.68
91.71
91.77
91.77
92.16
93.64
93.78
93.96
93.82
93.82
93.89
94.05
94.46
94.62
94.72
94.72
95.76
96.14
97.11
97.19
97.43
97.43
97.56
97.66
97.75
97.82
97.82
97.82
98.35
98.19
98.19
98.21
98.22
98.26
98.23
98.26
98.5
98.51
98.51
98.51
98.89
99.55
99.9
100.12
100.09
100.09
100.09
100.46
100.71
100.79
100.79
100.93
101.15
101.53
101.91
102.18
102.24
102.2
102.32
102.43
102.45
102.84
102.96
102.96
103.1
103.4
103.74
103.97
104.29
104.33
104.46
104.9
105.31
105.63
105.68




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=292313&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=292313&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292313&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[80,85[82.510.0083330.0083330.001667
[85,90[87.5370.3083330.3166670.061667
[90,95[92.5230.1916670.5083330.038333
[95,100[97.5270.2250.7333330.045
[100,105[102.5290.2416670.9750.048333
[105,110]107.530.02510.005

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[80,85[ & 82.5 & 1 & 0.008333 & 0.008333 & 0.001667 \tabularnewline
[85,90[ & 87.5 & 37 & 0.308333 & 0.316667 & 0.061667 \tabularnewline
[90,95[ & 92.5 & 23 & 0.191667 & 0.508333 & 0.038333 \tabularnewline
[95,100[ & 97.5 & 27 & 0.225 & 0.733333 & 0.045 \tabularnewline
[100,105[ & 102.5 & 29 & 0.241667 & 0.975 & 0.048333 \tabularnewline
[105,110] & 107.5 & 3 & 0.025 & 1 & 0.005 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=292313&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]1[/C][C]0.008333[/C][C]0.008333[/C][C]0.001667[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]37[/C][C]0.308333[/C][C]0.316667[/C][C]0.061667[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]23[/C][C]0.191667[/C][C]0.508333[/C][C]0.038333[/C][/ROW]
[ROW][C][95,100[[/C][C]97.5[/C][C]27[/C][C]0.225[/C][C]0.733333[/C][C]0.045[/C][/ROW]
[ROW][C][100,105[[/C][C]102.5[/C][C]29[/C][C]0.241667[/C][C]0.975[/C][C]0.048333[/C][/ROW]
[ROW][C][105,110][/C][C]107.5[/C][C]3[/C][C]0.025[/C][C]1[/C][C]0.005[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=292313&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292313&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[82.510.0083330.0083330.001667
[85,90[87.5370.3083330.3166670.061667
[90,95[92.5230.1916670.5083330.038333
[95,100[97.5270.2250.7333330.045
[100,105[102.5290.2416670.9750.048333
[105,110]107.530.02510.005



Parameters (Session):
par1 = 6 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 6 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- ''
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')
}