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, 10 Dec 2014 13:05:51 +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/2014/Dec/10/t14182167846bv0ppzbkw62t0e.htm/, Retrieved Wed, 29 May 2024 06:43:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265091, Retrieved Wed, 29 May 2024 06:43:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [1.1 AMSI - histogram] [2014-12-09 11:36:56] [4d39cf209776852399955073f9d0ee7a]
- R  D  [Histogram] [1.1 AMSE : Histog...] [2014-12-10 13:00:22] [765bd0d5d4a0c852014c120c6930661d]
-    D      [Histogram] [1.1 AMSE : Histog...] [2014-12-10 13:05:51] [706bcb1d0c5210dc074174906fafd7a3] [Current]
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Dataseries X:
NA
NA
NA
NA
57
NA
NA
63
NA
65
47
NA
NA
NA
NA
NA
NA
NA
NA
68
NA
NA
NA
NA
NA
NA
71
NA
NA
NA
NA
NA
59
68
48
NA
59
60
59
NA
79
NA
NA
59
NA
NA
NA
71
57
66
63
NA
58
NA
48
NA
73
NA
61
68
NA
62
NA
NA
NA
NA
NA
62
NA
69
58
58
NA
72
NA
62
65
69
66
NA
NA
NA
NA
66
55
NA
72
62
64
64
NA
NA
68
70
NA
69
NA
NA
NA
73
NA
NA
NA
74
78
75
NA
NA
50
NA
NA
65
78
78
NA
NA
70
63
63
NA
NA
67
66
62
NA
NA
NA
NA
73
NA
NA
NA
69
84
NA
58
NA
NA
NA
57
NA
68
NA
NA
69
NA
60
NA
66
NA
81
72
NA
NA
74
NA
NA
65
NA
51
80
NA
NA
74
NA
70
69
NA
55
71
NA
NA
NA
69
NA
NA
NA
NA
63
NA
39
68
NA
68
NA
67
70
NA
66
NA
NA
59
62
75
NA
73
NA
NA
NA
NA
73
NA
61
NA
63
78
65
77
69
68
NA
NA
NA
76
67
69
59
73
NA
NA
NA
NA
78
NA
68
NA
NA
68
NA
67
55
73
66
75
77
NA
75
57
NA
NA
NA
NA
66
NA
NA
60
64
74
59
NA
69
63
73
55
77
70
NA
NA
NA
66
77
NA
78
NA
NA
NA
NA
NA
72
50
72
71
80
NA
64
69
NA
75
79
NA
60
NA
NA
53
NA
69
NA
68
NA
NA
NA
73
NA
NA
64
NA
NA
NA
NA
79
NA
76
66
NA
57
NA
NA
58
74
NA
NA
NA
NA
62
NA
NA
NA
NA
66
66
NA
65
NA
NA
66
NA
77
NA
65
67
NA
NA
NA
NA
84
58
NA
75
NA
72
NA
NA
NA
NA
NA
NA
NA
NA
75
NA
72
75
NA
NA
NA
NA
NA
NA
NA
72
NA
NA
NA
72
NA
NA
NA
NA
75
NA
NA
66
73
NA
NA
NA
NA
70
NA
64
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA




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=265091&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=265091&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265091&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
[35,40[37.510.0025130.0025130.001183
[40,45[42.5000.0025130
[45,50[47.530.0075380.010050.00355
[50,55[52.540.010050.0201010.004734
[55,60[57.5220.0552760.0753770.026036
[60,65[62.5260.0653270.1407040.030769
[65,70[67.5490.1231160.2638190.057988
[70,75[72.5340.0854270.3492460.040237
[75,80[77.5250.0628140.412060.029586
[80,85]82.550.0125630.4246230.005917

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[35,40[ & 37.5 & 1 & 0.002513 & 0.002513 & 0.001183 \tabularnewline
[40,45[ & 42.5 & 0 & 0 & 0.002513 & 0 \tabularnewline
[45,50[ & 47.5 & 3 & 0.007538 & 0.01005 & 0.00355 \tabularnewline
[50,55[ & 52.5 & 4 & 0.01005 & 0.020101 & 0.004734 \tabularnewline
[55,60[ & 57.5 & 22 & 0.055276 & 0.075377 & 0.026036 \tabularnewline
[60,65[ & 62.5 & 26 & 0.065327 & 0.140704 & 0.030769 \tabularnewline
[65,70[ & 67.5 & 49 & 0.123116 & 0.263819 & 0.057988 \tabularnewline
[70,75[ & 72.5 & 34 & 0.085427 & 0.349246 & 0.040237 \tabularnewline
[75,80[ & 77.5 & 25 & 0.062814 & 0.41206 & 0.029586 \tabularnewline
[80,85] & 82.5 & 5 & 0.012563 & 0.424623 & 0.005917 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265091&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][35,40[[/C][C]37.5[/C][C]1[/C][C]0.002513[/C][C]0.002513[/C][C]0.001183[/C][/ROW]
[ROW][C][40,45[[/C][C]42.5[/C][C]0[/C][C]0[/C][C]0.002513[/C][C]0[/C][/ROW]
[ROW][C][45,50[[/C][C]47.5[/C][C]3[/C][C]0.007538[/C][C]0.01005[/C][C]0.00355[/C][/ROW]
[ROW][C][50,55[[/C][C]52.5[/C][C]4[/C][C]0.01005[/C][C]0.020101[/C][C]0.004734[/C][/ROW]
[ROW][C][55,60[[/C][C]57.5[/C][C]22[/C][C]0.055276[/C][C]0.075377[/C][C]0.026036[/C][/ROW]
[ROW][C][60,65[[/C][C]62.5[/C][C]26[/C][C]0.065327[/C][C]0.140704[/C][C]0.030769[/C][/ROW]
[ROW][C][65,70[[/C][C]67.5[/C][C]49[/C][C]0.123116[/C][C]0.263819[/C][C]0.057988[/C][/ROW]
[ROW][C][70,75[[/C][C]72.5[/C][C]34[/C][C]0.085427[/C][C]0.349246[/C][C]0.040237[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]25[/C][C]0.062814[/C][C]0.41206[/C][C]0.029586[/C][/ROW]
[ROW][C][80,85][/C][C]82.5[/C][C]5[/C][C]0.012563[/C][C]0.424623[/C][C]0.005917[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265091&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265091&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
[35,40[37.510.0025130.0025130.001183
[40,45[42.5000.0025130
[45,50[47.530.0075380.010050.00355
[50,55[52.540.010050.0201010.004734
[55,60[57.5220.0552760.0753770.026036
[60,65[62.5260.0653270.1407040.030769
[65,70[67.5490.1231160.2638190.057988
[70,75[72.5340.0854270.3492460.040237
[75,80[77.5250.0628140.412060.029586
[80,85]82.550.0125630.4246230.005917



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):
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 {
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')
}