Free Statistics

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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, 21 Dec 2011 07:21:28 -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/Dec/21/t1324470149dijgb6we9sggfgy.htm/, Retrieved Tue, 07 May 2024 07:19:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=158578, Retrieved Tue, 07 May 2024 07:19:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact74
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2011-12-21 12:21:28] [bbaf0bbad09b34135f8973992e5d67ea] [Current]
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Dataseries X:
149
139
115
83
137
114
120
89
85
94
115
134
116
97
118
121
80
135
110
131
108
112
154
126
103
69
81
96
137
102
122
126
108
151
105
120
122
111
122
39
112
123
54
105
98
113
65
111
95
55
84
86
100
82
88
117
49
146
87
87
93
114
73
93
87
130
117
99
95
85
106
160
125
96
83
102
94
94
82
111
119
101
148
132
122
94
107
85
117
111
118
93
74
124
120
95
120
58
109
112
96
90
124
118
133
140
92
66
109
114
122
104
72
89
106
100
110
103
114
58
84
51
61
79
160
99
92
80
125
59
55
95
117
50
96
133
54
120
37
70
58
78
87
91
115
53
107
86
67
104
126
155
76
116
128
120
158
93
89
105
98
81
85
100
83
143
97
113
123
130
89
119
85
110
76
86
91
96
118
108
56
51
71
110
112
48
98
124
81
109
116
96
58
45
105
85
80
106
71
93
101
104
98
88
59
77
73
118
109
103
77
97
86
114
53
72
54
77
95
137
77
64
48
96
103
75
92
73
52
52
51
70
60
68
67
84
128
69
70
62
85
83
71
84
87
81
62
123
91
63
94
101
87
82
75
71
60
102
102
87
48
93
74
76
78
98
77
91
169
80
71
105
56
92
91
64
86
69
76
115
88
105
77
76
100
54
69
83
81




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158578&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158578&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158578&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'Herman Ole Andreas Wold' @ wold.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[30,40[3520.006920.006920.000692
[40,50[4550.0173010.0242210.00173
[50,60[55220.0761250.1003460.007612
[60,70[65170.0588240.159170.005882
[70,80[75310.1072660.2664360.010727
[80,90[85470.162630.4290660.016263
[90,100[95430.1487890.5778550.014879
[100,110[105360.1245670.7024220.012457
[110,120[115370.1280280.830450.012803
[120,130[125250.0865050.9169550.008651
[130,140[135120.0415220.9584780.004152
[140,150[14550.0173010.9757790.00173
[150,160[15540.0138410.9896190.001384
[160,170]16530.01038110.001038

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[30,40[ & 35 & 2 & 0.00692 & 0.00692 & 0.000692 \tabularnewline
[40,50[ & 45 & 5 & 0.017301 & 0.024221 & 0.00173 \tabularnewline
[50,60[ & 55 & 22 & 0.076125 & 0.100346 & 0.007612 \tabularnewline
[60,70[ & 65 & 17 & 0.058824 & 0.15917 & 0.005882 \tabularnewline
[70,80[ & 75 & 31 & 0.107266 & 0.266436 & 0.010727 \tabularnewline
[80,90[ & 85 & 47 & 0.16263 & 0.429066 & 0.016263 \tabularnewline
[90,100[ & 95 & 43 & 0.148789 & 0.577855 & 0.014879 \tabularnewline
[100,110[ & 105 & 36 & 0.124567 & 0.702422 & 0.012457 \tabularnewline
[110,120[ & 115 & 37 & 0.128028 & 0.83045 & 0.012803 \tabularnewline
[120,130[ & 125 & 25 & 0.086505 & 0.916955 & 0.008651 \tabularnewline
[130,140[ & 135 & 12 & 0.041522 & 0.958478 & 0.004152 \tabularnewline
[140,150[ & 145 & 5 & 0.017301 & 0.975779 & 0.00173 \tabularnewline
[150,160[ & 155 & 4 & 0.013841 & 0.989619 & 0.001384 \tabularnewline
[160,170] & 165 & 3 & 0.010381 & 1 & 0.001038 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158578&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][30,40[[/C][C]35[/C][C]2[/C][C]0.00692[/C][C]0.00692[/C][C]0.000692[/C][/ROW]
[ROW][C][40,50[[/C][C]45[/C][C]5[/C][C]0.017301[/C][C]0.024221[/C][C]0.00173[/C][/ROW]
[ROW][C][50,60[[/C][C]55[/C][C]22[/C][C]0.076125[/C][C]0.100346[/C][C]0.007612[/C][/ROW]
[ROW][C][60,70[[/C][C]65[/C][C]17[/C][C]0.058824[/C][C]0.15917[/C][C]0.005882[/C][/ROW]
[ROW][C][70,80[[/C][C]75[/C][C]31[/C][C]0.107266[/C][C]0.266436[/C][C]0.010727[/C][/ROW]
[ROW][C][80,90[[/C][C]85[/C][C]47[/C][C]0.16263[/C][C]0.429066[/C][C]0.016263[/C][/ROW]
[ROW][C][90,100[[/C][C]95[/C][C]43[/C][C]0.148789[/C][C]0.577855[/C][C]0.014879[/C][/ROW]
[ROW][C][100,110[[/C][C]105[/C][C]36[/C][C]0.124567[/C][C]0.702422[/C][C]0.012457[/C][/ROW]
[ROW][C][110,120[[/C][C]115[/C][C]37[/C][C]0.128028[/C][C]0.83045[/C][C]0.012803[/C][/ROW]
[ROW][C][120,130[[/C][C]125[/C][C]25[/C][C]0.086505[/C][C]0.916955[/C][C]0.008651[/C][/ROW]
[ROW][C][130,140[[/C][C]135[/C][C]12[/C][C]0.041522[/C][C]0.958478[/C][C]0.004152[/C][/ROW]
[ROW][C][140,150[[/C][C]145[/C][C]5[/C][C]0.017301[/C][C]0.975779[/C][C]0.00173[/C][/ROW]
[ROW][C][150,160[[/C][C]155[/C][C]4[/C][C]0.013841[/C][C]0.989619[/C][C]0.001384[/C][/ROW]
[ROW][C][160,170][/C][C]165[/C][C]3[/C][C]0.010381[/C][C]1[/C][C]0.001038[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158578&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158578&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
[30,40[3520.006920.006920.000692
[40,50[4550.0173010.0242210.00173
[50,60[55220.0761250.1003460.007612
[60,70[65170.0588240.159170.005882
[70,80[75310.1072660.2664360.010727
[80,90[85470.162630.4290660.016263
[90,100[95430.1487890.5778550.014879
[100,110[105360.1245670.7024220.012457
[110,120[115370.1280280.830450.012803
[120,130[125250.0865050.9169550.008651
[130,140[135120.0415220.9584780.004152
[140,150[14550.0173010.9757790.00173
[150,160[15540.0138410.9896190.001384
[160,170]16530.01038110.001038



Parameters (Session):
par1 = 10 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 10 ; 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')
}