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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationFri, 30 Nov 2012 08:20:41 -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/2012/Nov/30/t1354281660lr1iyggp2rt0x1g.htm/, Retrieved Fri, 03 May 2024 23:25:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=195028, Retrieved Fri, 03 May 2024 23:25:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact57

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Boxplot and Trimmed Means] [Reddy Moores Boxp...] [2010-10-12 16:37:57] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R P   [Boxplot and Trimmed Means] [Reddy-Moores Plac...] [2010-10-13 09:46:26] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMPD    [Notched Boxplots] [] [2010-10-15 11:13:23] [b98453cac15ba1066b407e146608df68]
- RMPD        [Histogram] [] [2012-11-30 13:20:41] [564f08b1e01e129faa0d56ace254d273] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
127
108
110
NA
104
140
NA
115
121
112
NA
NA
105
111
151
NA
100
NA
NA
115
NA
124
69
NA
113
123
123
84
NA
121
NA
119
98
NA
NA
NA
109
NA
NA
129
119
119
122
NA
NA
82
NA
NA
114
NA
100
99
132
82
NA
107
114
110
NA
NA
109
106
124
NA
91
NA
NA
NA
128
98
133
NA
NA
124
142
96
93
NA
NA
NA
NA
92
NA
117
NA
NA
130
87
92
114
81
NA
115
123
115
117
NA
103
NA
NA
113
NA
117
133
NA
103
NA
117
113
127
126
119
97
105
140
NA
112
113
NA
92
98
122
100
84
142
NA
137
105
NA
NA
104
NA
NA
NA
NA
98
120
NA
NA
123
90
119
105
NA
135
101
NA
NA
NA
NA
114
122
132
NA
NA
NA
114
103
115
108
NA
105

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195028&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195028&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195028&T=0

As an alternative you can also use a QR Code:  
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'Gwilym Jenkins' @ jenkins.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[60,70]6510.0061730.0061730.00102
]70,80]75000.0061730
]80,90]8570.043210.0493830.007143
]90,100]95150.0925930.1419750.015306
]100,110]105190.1172840.2592590.019388
]110,120]115270.1666670.4259260.027551
]120,130]125180.1111110.5370370.018367
]130,140]13580.0493830.586420.008163
]140,150]14520.0123460.5987650.002041
]150,160]15510.0061730.6049380.00102

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[60,70] & 65 & 1 & 0.006173 & 0.006173 & 0.00102 \tabularnewline
]70,80] & 75 & 0 & 0 & 0.006173 & 0 \tabularnewline
]80,90] & 85 & 7 & 0.04321 & 0.049383 & 0.007143 \tabularnewline
]90,100] & 95 & 15 & 0.092593 & 0.141975 & 0.015306 \tabularnewline
]100,110] & 105 & 19 & 0.117284 & 0.259259 & 0.019388 \tabularnewline
]110,120] & 115 & 27 & 0.166667 & 0.425926 & 0.027551 \tabularnewline
]120,130] & 125 & 18 & 0.111111 & 0.537037 & 0.018367 \tabularnewline
]130,140] & 135 & 8 & 0.049383 & 0.58642 & 0.008163 \tabularnewline
]140,150] & 145 & 2 & 0.012346 & 0.598765 & 0.002041 \tabularnewline
]150,160] & 155 & 1 & 0.006173 & 0.604938 & 0.00102 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195028&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][60,70][/C][C]65[/C][C]1[/C][C]0.006173[/C][C]0.006173[/C][C]0.00102[/C][/ROW]
[ROW][C]]70,80][/C][C]75[/C][C]0[/C][C]0[/C][C]0.006173[/C][C]0[/C][/ROW]
[ROW][C]]80,90][/C][C]85[/C][C]7[/C][C]0.04321[/C][C]0.049383[/C][C]0.007143[/C][/ROW]
[ROW][C]]90,100][/C][C]95[/C][C]15[/C][C]0.092593[/C][C]0.141975[/C][C]0.015306[/C][/ROW]
[ROW][C]]100,110][/C][C]105[/C][C]19[/C][C]0.117284[/C][C]0.259259[/C][C]0.019388[/C][/ROW]
[ROW][C]]110,120][/C][C]115[/C][C]27[/C][C]0.166667[/C][C]0.425926[/C][C]0.027551[/C][/ROW]
[ROW][C]]120,130][/C][C]125[/C][C]18[/C][C]0.111111[/C][C]0.537037[/C][C]0.018367[/C][/ROW]
[ROW][C]]130,140][/C][C]135[/C][C]8[/C][C]0.049383[/C][C]0.58642[/C][C]0.008163[/C][/ROW]
[ROW][C]]140,150][/C][C]145[/C][C]2[/C][C]0.012346[/C][C]0.598765[/C][C]0.002041[/C][/ROW]
[ROW][C]]150,160][/C][C]155[/C][C]1[/C][C]0.006173[/C][C]0.604938[/C][C]0.00102[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195028&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195028&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[60,70]6510.0061730.0061730.00102
]70,80]75000.0061730
]80,90]8570.043210.0493830.007143
]90,100]95150.0925930.1419750.015306
]100,110]105190.1172840.2592590.019388
]110,120]115270.1666670.4259260.027551
]120,130]125180.1111110.5370370.018367
]130,140]13580.0493830.586420.008163
]140,150]14520.0123460.5987650.002041
]150,160]15510.0061730.6049380.00102


Figures (Output of Computation)

Input Parameters & R Code

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