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Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSun, 09 Feb 2014 06:26:05 -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/2014/Feb/09/t1391945186axfd93q3mcvktt7.htm/, Retrieved Thu, 16 May 2024 21:53:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=233404, Retrieved Thu, 16 May 2024 21:53:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2014-02-09 11:26:05] [7924821bfd3c647737470140bc76edc8] [Current]
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Dataseries X:
71.97
72.32
74.07
77.95
81.75
80.81
74.1
71.37
75.21
76.9
74.44
74.76
76.23
76.97
78.4
78.6
80.08
81.12
80.31
84.59
81.34
80.95
80.48
75.26
76.32
78.92
80.47
83.14
85.42
81.53
87.31
86.01
85.1
79.91
78.6
78.6
79.37
82.89
84.43
85.32
87.71
84.68
80.62
84.79
85.49
81.68
77.69
78.31
79.18
80.91
83.91
86.3
89.76
85.11
83.81
85.36
85.89
82.59
80.87
80.27
81.36
84.81
90.3
95.43
97.59
97.8
99.48
97.52
104.39
97.74
91.37
92.42
96.9
101.58
105.46
110.06
107.9
102.87
96.28
98.59
103.22
98.6
91.79
93.83
95.17
95.19
99.44
109.18
109.15
109.72
108.41
102.96
107.64
97.28
97.25
91.84
94.12
97.86
98.83
102.29
104.49
102.11
102.14
101.28
101.21
94.2
88.47
88.08
88.02
92.95
97.05
101.44
100.34
99.98
94.17
94.54
95.12
98.04
93.72
93.83
93.03
95.81
99.1
100.12
100.67
103.87
102.39
107.21
105.71
99.79
96.12
96.17
97.23
98.08
99.84
99.72
99.92
102.7
102.06
102.36
102.43
100.6
98.4
98.61
103.03
104.7
107.45
109.67
110.54
112.05
113.19
114.2
112.56
107.36
103.93
103.83
104.74
107.5
109.53
109.42
108.6
110.72
105.1
105.19
102.55
101.25
101.56
101.62
101.7
102.94
104.37
106.93
107.82
110.83
106.86
109.46
108.8
108.69
107.77
108.64
108.5
113.84
114.59
116.27
113.63
112.29
110.31
108.47
110.67
109.1
107.02
108.12
106.69
109.87
110.82
114.14
113.31
115.16
111.06
111.13
115.96
117.57
114.69
119.42
118.4
123.32
123.39
127.04
129.35
127.12
122.1
120.22
121.53
119.01
114.27
114.46




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=233404&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]2 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=233404&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=233404&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 time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[70,75[72.570.0324070.0324070.006481
[75,80[77.5170.0787040.1111110.015741
[80,85[82.5260.120370.2314810.024074
[85,90[87.5150.0694440.3009260.013889
[90,95[92.5140.0648150.3657410.012963
[95,100[97.5330.1527780.5185190.030556
[100,105[102.5340.1574070.6759260.031481
[105,110[107.5330.1527780.8287040.030556
[110,115[112.5220.1018520.9305560.02037
[115,120[117.570.0324070.9629630.006481
[120,125[122.550.0231480.9861110.00463
[125,130]127.530.01388910.002778

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[70,75[ & 72.5 & 7 & 0.032407 & 0.032407 & 0.006481 \tabularnewline
[75,80[ & 77.5 & 17 & 0.078704 & 0.111111 & 0.015741 \tabularnewline
[80,85[ & 82.5 & 26 & 0.12037 & 0.231481 & 0.024074 \tabularnewline
[85,90[ & 87.5 & 15 & 0.069444 & 0.300926 & 0.013889 \tabularnewline
[90,95[ & 92.5 & 14 & 0.064815 & 0.365741 & 0.012963 \tabularnewline
[95,100[ & 97.5 & 33 & 0.152778 & 0.518519 & 0.030556 \tabularnewline
[100,105[ & 102.5 & 34 & 0.157407 & 0.675926 & 0.031481 \tabularnewline
[105,110[ & 107.5 & 33 & 0.152778 & 0.828704 & 0.030556 \tabularnewline
[110,115[ & 112.5 & 22 & 0.101852 & 0.930556 & 0.02037 \tabularnewline
[115,120[ & 117.5 & 7 & 0.032407 & 0.962963 & 0.006481 \tabularnewline
[120,125[ & 122.5 & 5 & 0.023148 & 0.986111 & 0.00463 \tabularnewline
[125,130] & 127.5 & 3 & 0.013889 & 1 & 0.002778 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=233404&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][70,75[[/C][C]72.5[/C][C]7[/C][C]0.032407[/C][C]0.032407[/C][C]0.006481[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]17[/C][C]0.078704[/C][C]0.111111[/C][C]0.015741[/C][/ROW]
[ROW][C][80,85[[/C][C]82.5[/C][C]26[/C][C]0.12037[/C][C]0.231481[/C][C]0.024074[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]15[/C][C]0.069444[/C][C]0.300926[/C][C]0.013889[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]14[/C][C]0.064815[/C][C]0.365741[/C][C]0.012963[/C][/ROW]
[ROW][C][95,100[[/C][C]97.5[/C][C]33[/C][C]0.152778[/C][C]0.518519[/C][C]0.030556[/C][/ROW]
[ROW][C][100,105[[/C][C]102.5[/C][C]34[/C][C]0.157407[/C][C]0.675926[/C][C]0.031481[/C][/ROW]
[ROW][C][105,110[[/C][C]107.5[/C][C]33[/C][C]0.152778[/C][C]0.828704[/C][C]0.030556[/C][/ROW]
[ROW][C][110,115[[/C][C]112.5[/C][C]22[/C][C]0.101852[/C][C]0.930556[/C][C]0.02037[/C][/ROW]
[ROW][C][115,120[[/C][C]117.5[/C][C]7[/C][C]0.032407[/C][C]0.962963[/C][C]0.006481[/C][/ROW]
[ROW][C][120,125[[/C][C]122.5[/C][C]5[/C][C]0.023148[/C][C]0.986111[/C][C]0.00463[/C][/ROW]
[ROW][C][125,130][/C][C]127.5[/C][C]3[/C][C]0.013889[/C][C]1[/C][C]0.002778[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=233404&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=233404&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
[70,75[72.570.0324070.0324070.006481
[75,80[77.5170.0787040.1111110.015741
[80,85[82.5260.120370.2314810.024074
[85,90[87.5150.0694440.3009260.013889
[90,95[92.5140.0648150.3657410.012963
[95,100[97.5330.1527780.5185190.030556
[100,105[102.5340.1574070.6759260.031481
[105,110[107.5330.1527780.8287040.030556
[110,115[112.5220.1018520.9305560.02037
[115,120[117.570.0324070.9629630.006481
[120,125[122.550.0231480.9861110.00463
[125,130]127.530.01388910.002778



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')
}