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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 computationThu, 11 Dec 2014 12:23:11 +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/11/t1418300626gkfe5c8bban688i.htm/, Retrieved Thu, 31 Oct 2024 22:51:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265866, Retrieved Thu, 31 Oct 2024 22:51:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [histogram H] [2014-12-11 12:23:11] [d71ad52285d92a63edfc83f9fb1da7a1] [Current]
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Dataseries X:
86
62
70
71
108
64
119
97
129
153
78
80
99
68
147
40
57
120
71
84
68
55
137
79
116
101
111
189
66
81
63
69
71
70
64
143
85
86
55
69
120
96
60
95
100
68
57
105
85
103
57
51
69
41
49
50
93
58
54
74
15
69
107
65
58
107
70
53
136
126
95
69
136
58
59
118
110
82
50
102
65
90
64
83
70
50
77
37
81
101
79
71
60
55
44
40
56
43
45
32
56
40
34
89
50
56
46
76
64
74
57
45
30
62
51
36
34
61
70
69
145
23
120
147
215
24
84
30
77
46
61
178
160
57
42
163
75
94
45
78
47
29
97
116
32
50
118
66
48
86
89
76
39
75
57
72
60
109
76
65
40
58
123
71
102
80
97
46
93
19
140
78
98
40
80
76
79
87
95
49
49
80
86
69
79
52
120
69
94
72
43
87
52
71
61
51
50
67
30
70
52
75
87
69
72
79
121
43
58
57
50
69
64
38
53
90
96
49
56
102
40
100
67
78
62
55
59
96
86
38
43
23
77
48
26
91
94
62
74
114
52
64
31
38
27
105
64
62
65
58
76
140
48
68
80
71
76
63
46
53
74
70
78
56
100
51
52
102
78
78
55
98
76
73
47
45
83
60
48
50
56
77
91
76
68
74
29




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=265866&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=265866&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265866&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
[0,20[1020.0069690.0069690.000348
[20,40[30210.0731710.0801390.003659
[40,60[50780.2717770.3519160.013589
[60,80[70940.3275260.6794430.016376
[80,100[90450.1567940.8362370.00784
[100,120[110240.0836240.9198610.004181
[120,140[130110.0383280.9581880.001916
[140,160[15070.024390.9825780.00122
[160,180[17030.0104530.9930310.000523
[180,200[19010.0034840.9965160.000174
[200,220]21010.00348410.000174

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,20[ & 10 & 2 & 0.006969 & 0.006969 & 0.000348 \tabularnewline
[20,40[ & 30 & 21 & 0.073171 & 0.080139 & 0.003659 \tabularnewline
[40,60[ & 50 & 78 & 0.271777 & 0.351916 & 0.013589 \tabularnewline
[60,80[ & 70 & 94 & 0.327526 & 0.679443 & 0.016376 \tabularnewline
[80,100[ & 90 & 45 & 0.156794 & 0.836237 & 0.00784 \tabularnewline
[100,120[ & 110 & 24 & 0.083624 & 0.919861 & 0.004181 \tabularnewline
[120,140[ & 130 & 11 & 0.038328 & 0.958188 & 0.001916 \tabularnewline
[140,160[ & 150 & 7 & 0.02439 & 0.982578 & 0.00122 \tabularnewline
[160,180[ & 170 & 3 & 0.010453 & 0.993031 & 0.000523 \tabularnewline
[180,200[ & 190 & 1 & 0.003484 & 0.996516 & 0.000174 \tabularnewline
[200,220] & 210 & 1 & 0.003484 & 1 & 0.000174 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265866&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][0,20[[/C][C]10[/C][C]2[/C][C]0.006969[/C][C]0.006969[/C][C]0.000348[/C][/ROW]
[ROW][C][20,40[[/C][C]30[/C][C]21[/C][C]0.073171[/C][C]0.080139[/C][C]0.003659[/C][/ROW]
[ROW][C][40,60[[/C][C]50[/C][C]78[/C][C]0.271777[/C][C]0.351916[/C][C]0.013589[/C][/ROW]
[ROW][C][60,80[[/C][C]70[/C][C]94[/C][C]0.327526[/C][C]0.679443[/C][C]0.016376[/C][/ROW]
[ROW][C][80,100[[/C][C]90[/C][C]45[/C][C]0.156794[/C][C]0.836237[/C][C]0.00784[/C][/ROW]
[ROW][C][100,120[[/C][C]110[/C][C]24[/C][C]0.083624[/C][C]0.919861[/C][C]0.004181[/C][/ROW]
[ROW][C][120,140[[/C][C]130[/C][C]11[/C][C]0.038328[/C][C]0.958188[/C][C]0.001916[/C][/ROW]
[ROW][C][140,160[[/C][C]150[/C][C]7[/C][C]0.02439[/C][C]0.982578[/C][C]0.00122[/C][/ROW]
[ROW][C][160,180[[/C][C]170[/C][C]3[/C][C]0.010453[/C][C]0.993031[/C][C]0.000523[/C][/ROW]
[ROW][C][180,200[[/C][C]190[/C][C]1[/C][C]0.003484[/C][C]0.996516[/C][C]0.000174[/C][/ROW]
[ROW][C][200,220][/C][C]210[/C][C]1[/C][C]0.003484[/C][C]1[/C][C]0.000174[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265866&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265866&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
[0,20[1020.0069690.0069690.000348
[20,40[30210.0731710.0801390.003659
[40,60[50780.2717770.3519160.013589
[60,80[70940.3275260.6794430.016376
[80,100[90450.1567940.8362370.00784
[100,120[110240.0836240.9198610.004181
[120,140[130110.0383280.9581880.001916
[140,160[15070.024390.9825780.00122
[160,180[17030.0104530.9930310.000523
[180,200[19010.0034840.9965160.000174
[200,220]21010.00348410.000174



Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
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')
}