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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 computationWed, 16 Nov 2011 11:56:56 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/16/t1321462626jnzz4m04tyiy124.htm/, Retrieved Fri, 26 Apr 2024 20:26:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=144106, Retrieved Fri, 26 Apr 2024 20:26:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
F RMPD  [Mean Plot] [Colombia Coffee] [2008-01-07 13:38:24] [74be16979710d4c4e7c6647856088456]
- RMPD    [Histogram] [] [2011-11-16 15:37:27] [489eb911c8db04aca1fc54d886fc3144]
-   PD        [Histogram] [] [2011-11-16 16:56:56] [d160b678fd2d7bb562db2147d7efddc2] [Current]
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Dataseries X:
87,28
87,28
87,09
86,92
87,59
90,72
90,69
90,3
89,55
88,94
88,41
87,82
87,07
86,82
86,4
86,02
85,66
85,32
85
84,67
83,94
82,83
81,95
81,19
80,48
78,86
69,47
68,77
70,06
73,95
75,8
77,79
81,57
83,07
84,34
85,1
85,25
84,26
83,63
86,44
85,3
84,1
83,36
82,48
81,58
80,47
79,34
82,13
81,69
80,7
79,88
79,16
78,38
77,42
76,47
75,46
74,48
78,27
80,7
79,91
78,75
77,78
81,14
81,08
80,03
78,91
78,01
76,9
75,97
81,93
80,27
78,67
77,42
76,16
74,7
76,39
76,04
74,65
73,29
71,79
74,39
74,91
74,54
73,08
72,75
71,32
70,38
70,35
70,01
69,36
67,77
69,26
69,8
68,38
67,62
68,39
66,95
65,21
66,64
63,45
60,66
62,34
60,32
58,64
60,46
58,59
61,87
61,85
67,44
77,06
91,74
93,15
94,15
93,11
91,51
89,96
88,16
86,98
88,03
86,24
84,65
83,23
81,7
80,25
78,8
77,51
76,2
75,04
74
75,49
77,14
76,15
76,27
78,19
76,49
77,31
76,65
74,99
73,51
72,07
70,59
71,96
76,29
74,86
74,93
71,9
71,01
77,47
75,78
76,6
76,07
74,57
73,02
72,65
73,16
71,53
69,78
67,98
69,96
72,16
70,47
68,86
67,37
65,87
72,16
71,34
69,93
68,44
67,16
66,01
67,25
70,91
69,75
68,59
67,48
66,31
64,81
66,58
65,97
64,7
64,7
60,94
59,08
58,42
57,77
57,11
53,31
49,96
49,4
48,84
48,3
47,74
47,24
46,76
46,29
48,9
49,23
48,53
48,03
54,34
53,79
53,24
52,96
52,17
51,7
58,55
78,2
77,03
76,19
77,15
75,87
95,47
109,67
112,28
112,01
107,93
105,96
105,06
102,98
102,2
105,23
101,85
99,89
96,23
94,76
91,51
91,63
91,54
85,23
87,83
87,38
84,44
85,19
84,03
86,73
102,52
104,45
106,98
107,02
99,26
94,45
113,44
157,33
147,38
171,89
171,95
132,71
126,02
121,18
115,45
110,48
117,85
117,63
124,65
109,59
111,27
99,78
98,21
99,2
97,97
89,55
87,91
93,34
94,42
93,2
90,29
91,46
89,98
88,35
88,41
82,44
79,89
75,69
75,66
84,5
96,73
87,48
82,39
83,48
79,31
78,16
72,77
72,45
68,46
67,62
68,76
70,07
68,55
65,3
58,96
59,17
62,37
66,28
55,62
55,23
55,85
56,75
50,89
53,88
52,95
55,08
53,61
58,78
61,85
55,91
53,32
46,41
44,57
50
50
53,36
46,23
50,45
49,07
45,85
48,45
49,96
46,53
50,51
47,58
48,05
46,84
47,67
49,16
55,54
55,82
58,22
56,19
57,77
63,19
54,76
55,74
62,54
61,39
69,6
79,23
80
93,68
107,63
100,18
97,3
90,45
80,64
80,58
75,82
85,59
89,35
89,42
104,73
95,32
89,27
90,44
86,97
79,98
81,22
87,35
83,64
82,22
94,4
102,18




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=144106&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=144106&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144106&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
[40,50[45250.0694440.0694440.006944
[50,60[55400.1111110.1805560.011111
[60,70[65530.1472220.3277780.014722
[70,80[75930.2583330.5861110.025833
[80,90[85830.2305560.8166670.023056
[90,100[95330.0916670.9083330.009167
[100,110[105170.0472220.9555560.004722
[110,120[11580.0222220.9777780.002222
[120,130[12530.0083330.9861110.000833
[130,140[13510.0027780.9888890.000278
[140,150[14510.0027780.9916670.000278
[150,160[15510.0027780.9944440.000278
[160,170[165000.9944440
[170,180]17520.00555610.000556

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[40,50[ & 45 & 25 & 0.069444 & 0.069444 & 0.006944 \tabularnewline
[50,60[ & 55 & 40 & 0.111111 & 0.180556 & 0.011111 \tabularnewline
[60,70[ & 65 & 53 & 0.147222 & 0.327778 & 0.014722 \tabularnewline
[70,80[ & 75 & 93 & 0.258333 & 0.586111 & 0.025833 \tabularnewline
[80,90[ & 85 & 83 & 0.230556 & 0.816667 & 0.023056 \tabularnewline
[90,100[ & 95 & 33 & 0.091667 & 0.908333 & 0.009167 \tabularnewline
[100,110[ & 105 & 17 & 0.047222 & 0.955556 & 0.004722 \tabularnewline
[110,120[ & 115 & 8 & 0.022222 & 0.977778 & 0.002222 \tabularnewline
[120,130[ & 125 & 3 & 0.008333 & 0.986111 & 0.000833 \tabularnewline
[130,140[ & 135 & 1 & 0.002778 & 0.988889 & 0.000278 \tabularnewline
[140,150[ & 145 & 1 & 0.002778 & 0.991667 & 0.000278 \tabularnewline
[150,160[ & 155 & 1 & 0.002778 & 0.994444 & 0.000278 \tabularnewline
[160,170[ & 165 & 0 & 0 & 0.994444 & 0 \tabularnewline
[170,180] & 175 & 2 & 0.005556 & 1 & 0.000556 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144106&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][40,50[[/C][C]45[/C][C]25[/C][C]0.069444[/C][C]0.069444[/C][C]0.006944[/C][/ROW]
[ROW][C][50,60[[/C][C]55[/C][C]40[/C][C]0.111111[/C][C]0.180556[/C][C]0.011111[/C][/ROW]
[ROW][C][60,70[[/C][C]65[/C][C]53[/C][C]0.147222[/C][C]0.327778[/C][C]0.014722[/C][/ROW]
[ROW][C][70,80[[/C][C]75[/C][C]93[/C][C]0.258333[/C][C]0.586111[/C][C]0.025833[/C][/ROW]
[ROW][C][80,90[[/C][C]85[/C][C]83[/C][C]0.230556[/C][C]0.816667[/C][C]0.023056[/C][/ROW]
[ROW][C][90,100[[/C][C]95[/C][C]33[/C][C]0.091667[/C][C]0.908333[/C][C]0.009167[/C][/ROW]
[ROW][C][100,110[[/C][C]105[/C][C]17[/C][C]0.047222[/C][C]0.955556[/C][C]0.004722[/C][/ROW]
[ROW][C][110,120[[/C][C]115[/C][C]8[/C][C]0.022222[/C][C]0.977778[/C][C]0.002222[/C][/ROW]
[ROW][C][120,130[[/C][C]125[/C][C]3[/C][C]0.008333[/C][C]0.986111[/C][C]0.000833[/C][/ROW]
[ROW][C][130,140[[/C][C]135[/C][C]1[/C][C]0.002778[/C][C]0.988889[/C][C]0.000278[/C][/ROW]
[ROW][C][140,150[[/C][C]145[/C][C]1[/C][C]0.002778[/C][C]0.991667[/C][C]0.000278[/C][/ROW]
[ROW][C][150,160[[/C][C]155[/C][C]1[/C][C]0.002778[/C][C]0.994444[/C][C]0.000278[/C][/ROW]
[ROW][C][160,170[[/C][C]165[/C][C]0[/C][C]0[/C][C]0.994444[/C][C]0[/C][/ROW]
[ROW][C][170,180][/C][C]175[/C][C]2[/C][C]0.005556[/C][C]1[/C][C]0.000556[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144106&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144106&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
[40,50[45250.0694440.0694440.006944
[50,60[55400.1111110.1805560.011111
[60,70[65530.1472220.3277780.014722
[70,80[75930.2583330.5861110.025833
[80,90[85830.2305560.8166670.023056
[90,100[95330.0916670.9083330.009167
[100,110[105170.0472220.9555560.004722
[110,120[11580.0222220.9777780.002222
[120,130[12530.0083330.9861110.000833
[130,140[13510.0027780.9888890.000278
[140,150[14510.0027780.9916670.000278
[150,160[15510.0027780.9944440.000278
[160,170[165000.9944440
[170,180]17520.00555610.000556



Parameters (Session):
par1 = 12 ;
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')
}