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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 15 Dec 2014 13:45:39 +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/15/t141865116803lqhb7oimehp8j.htm/, Retrieved Thu, 16 May 2024 12:18:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268385, Retrieved Thu, 16 May 2024 12:18:20 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [paper34] [2014-12-15 13:45:39] [0015a2406d94cac8c1a56a29b9122359] [Current]
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Dataseries X:
26
51
57
37
67
43
52
52
43
84
67
49
70
52
58
68
43
56
74
65
63
58
57
63
53
64
53
29
54
51
58
43
51
53
54
61
47
39
48
50
35
68
49
67
43
62
57
54
61
56
41
43
53
66
58
46
51
51
45
37
59
42
66
53
52
16
46
56
50
59
60
52
44
67
52
55
37
54
51
48
60
50
63
33
67
46
54
59
61
47
69
52
55
55
41
73
51
52
50
51
60
56
56
29
73
55
43
61
56
56
47
25
46
51
48
47
58
51
55
57
60
56
49
43
59
58
53
48
51
59
62
51
64
52
50
54
58
63
31
71
54
43
41
63
63
56
51
41
66
44
58
51
57
30
46
51
56
58
44
14
53
42
44
30
46
50
54
48
55
35
55
41
59
54
66
55
45
51
47
42
53
53
41
55
55
46
63
43
65
59
39
44
57
69
46
46
40
70
54
77
60
50
66
60
51
69
60
58
39
51
52
49
63
51
52
52
31
61
54
72
65
56
63
45
52
68
45
70
69
46
39
54
41
68
63
57
61
39
59
51
51
65
50
21
47
37
58
51
40
64
58
56
63
60
64
47
46
50
46
44
58
58
25
56
56
59
46
49
53
58
54
52
59




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=268385&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=268385&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268385&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
[10,15[12.510.0036630.0036630.000733
[15,20[17.510.0036630.0073260.000733
[20,25[22.510.0036630.0109890.000733
[25,30[27.550.0183150.0293040.003663
[30,35[32.550.0183150.0476190.003663
[35,40[37.5110.0402930.0879120.008059
[40,45[42.5280.1025640.1904760.020513
[45,50[47.5340.1245420.3150180.024908
[50,55[52.5680.2490840.5641030.049817
[55,60[57.5560.2051280.7692310.041026
[60,65[62.5310.1135530.8827840.022711
[65,70[67.5220.0805860.963370.016117
[70,75[72.580.0293040.9926740.005861
[75,80[77.510.0036630.9963370.000733
[80,85]82.510.00366310.000733

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[10,15[ & 12.5 & 1 & 0.003663 & 0.003663 & 0.000733 \tabularnewline
[15,20[ & 17.5 & 1 & 0.003663 & 0.007326 & 0.000733 \tabularnewline
[20,25[ & 22.5 & 1 & 0.003663 & 0.010989 & 0.000733 \tabularnewline
[25,30[ & 27.5 & 5 & 0.018315 & 0.029304 & 0.003663 \tabularnewline
[30,35[ & 32.5 & 5 & 0.018315 & 0.047619 & 0.003663 \tabularnewline
[35,40[ & 37.5 & 11 & 0.040293 & 0.087912 & 0.008059 \tabularnewline
[40,45[ & 42.5 & 28 & 0.102564 & 0.190476 & 0.020513 \tabularnewline
[45,50[ & 47.5 & 34 & 0.124542 & 0.315018 & 0.024908 \tabularnewline
[50,55[ & 52.5 & 68 & 0.249084 & 0.564103 & 0.049817 \tabularnewline
[55,60[ & 57.5 & 56 & 0.205128 & 0.769231 & 0.041026 \tabularnewline
[60,65[ & 62.5 & 31 & 0.113553 & 0.882784 & 0.022711 \tabularnewline
[65,70[ & 67.5 & 22 & 0.080586 & 0.96337 & 0.016117 \tabularnewline
[70,75[ & 72.5 & 8 & 0.029304 & 0.992674 & 0.005861 \tabularnewline
[75,80[ & 77.5 & 1 & 0.003663 & 0.996337 & 0.000733 \tabularnewline
[80,85] & 82.5 & 1 & 0.003663 & 1 & 0.000733 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268385&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][10,15[[/C][C]12.5[/C][C]1[/C][C]0.003663[/C][C]0.003663[/C][C]0.000733[/C][/ROW]
[ROW][C][15,20[[/C][C]17.5[/C][C]1[/C][C]0.003663[/C][C]0.007326[/C][C]0.000733[/C][/ROW]
[ROW][C][20,25[[/C][C]22.5[/C][C]1[/C][C]0.003663[/C][C]0.010989[/C][C]0.000733[/C][/ROW]
[ROW][C][25,30[[/C][C]27.5[/C][C]5[/C][C]0.018315[/C][C]0.029304[/C][C]0.003663[/C][/ROW]
[ROW][C][30,35[[/C][C]32.5[/C][C]5[/C][C]0.018315[/C][C]0.047619[/C][C]0.003663[/C][/ROW]
[ROW][C][35,40[[/C][C]37.5[/C][C]11[/C][C]0.040293[/C][C]0.087912[/C][C]0.008059[/C][/ROW]
[ROW][C][40,45[[/C][C]42.5[/C][C]28[/C][C]0.102564[/C][C]0.190476[/C][C]0.020513[/C][/ROW]
[ROW][C][45,50[[/C][C]47.5[/C][C]34[/C][C]0.124542[/C][C]0.315018[/C][C]0.024908[/C][/ROW]
[ROW][C][50,55[[/C][C]52.5[/C][C]68[/C][C]0.249084[/C][C]0.564103[/C][C]0.049817[/C][/ROW]
[ROW][C][55,60[[/C][C]57.5[/C][C]56[/C][C]0.205128[/C][C]0.769231[/C][C]0.041026[/C][/ROW]
[ROW][C][60,65[[/C][C]62.5[/C][C]31[/C][C]0.113553[/C][C]0.882784[/C][C]0.022711[/C][/ROW]
[ROW][C][65,70[[/C][C]67.5[/C][C]22[/C][C]0.080586[/C][C]0.96337[/C][C]0.016117[/C][/ROW]
[ROW][C][70,75[[/C][C]72.5[/C][C]8[/C][C]0.029304[/C][C]0.992674[/C][C]0.005861[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]1[/C][C]0.003663[/C][C]0.996337[/C][C]0.000733[/C][/ROW]
[ROW][C][80,85][/C][C]82.5[/C][C]1[/C][C]0.003663[/C][C]1[/C][C]0.000733[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268385&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268385&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
[10,15[12.510.0036630.0036630.000733
[15,20[17.510.0036630.0073260.000733
[20,25[22.510.0036630.0109890.000733
[25,30[27.550.0183150.0293040.003663
[30,35[32.550.0183150.0476190.003663
[35,40[37.5110.0402930.0879120.008059
[40,45[42.5280.1025640.1904760.020513
[45,50[47.5340.1245420.3150180.024908
[50,55[52.5680.2490840.5641030.049817
[55,60[57.5560.2051280.7692310.041026
[60,65[62.5310.1135530.8827840.022711
[65,70[67.5220.0805860.963370.016117
[70,75[72.580.0293040.9926740.005861
[75,80[77.510.0036630.9963370.000733
[80,85]82.510.00366310.000733



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 {
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')
}