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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 computationMon, 27 Oct 2014 16:39:56 +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/Oct/27/t1414430031uje6pox3r0dx6lo.htm/, Retrieved Fri, 10 May 2024 14:25:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=247370, Retrieved Fri, 10 May 2024 14:25:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact38

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] [Care Age 10 Data] [2009-10-26 09:01:50] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD  [Boxplot and Trimmed Means] [Care Age 7 Data] [2009-10-26 18:36:29] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   P     [CARE Data - Boxplots and Scatterplot Matrix] [CARE Data] [2010-10-19 14:16:27] [3fdd735c61ad38cbc9b3393dc997cdb7]
- RM        [CARE Data - Boxplots and Scatterplot Matrix] [CARE data - works...] [2011-10-17 10:23:12] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMP         [Boxplot and Trimmed Means] [CARE Study Age 7 ] [2013-10-17 12:59:45] [34296d8f7657c52ed60d5bff9133afec]
- RMPD            [Histogram] [ARD] [2014-10-27 16:39:56] [179cc397bc7ba643a7ca8fd40ad387b9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
88
98
89
81
88
95
79
91
80
91
85
94
86
82
107
97
78
91
74
95
97
112
80
98
102
100
97
92
114
88
96
91
114
91
114
89
103
83
74
88
88
98
74
86
93
85
91
75
97
88
79
106
102
98
98
114
95
98
82
97
94
84
88
83
98
106
94
91
89
102
103
96
89
112
74
74
102
106
91
94
98
85
108
90
74
81
104
90
95
85
114
114
93
104
92
100
92
77
86
87
91
102
100
113

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'George Udny Yule' @ yule.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 & 0 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=247370&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=247370&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=247370&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 time0 seconds
R Server'George Udny Yule' @ yule.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[70,75[72.560.0576920.0576920.011538
[75,80[77.550.0480770.1057690.009615
[80,85[82.590.0865380.1923080.017308
[85,90[87.5190.1826920.3750.036538
[90,95[92.5200.1923080.5673080.038462
[95,100[97.5190.1826920.750.036538
[100,105[102.5120.1153850.8653850.023077
[105,110[107.550.0480770.9134620.009615
[110,115]112.590.08653810.017308

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[70,75[ & 72.5 & 6 & 0.057692 & 0.057692 & 0.011538 \tabularnewline
[75,80[ & 77.5 & 5 & 0.048077 & 0.105769 & 0.009615 \tabularnewline
[80,85[ & 82.5 & 9 & 0.086538 & 0.192308 & 0.017308 \tabularnewline
[85,90[ & 87.5 & 19 & 0.182692 & 0.375 & 0.036538 \tabularnewline
[90,95[ & 92.5 & 20 & 0.192308 & 0.567308 & 0.038462 \tabularnewline
[95,100[ & 97.5 & 19 & 0.182692 & 0.75 & 0.036538 \tabularnewline
[100,105[ & 102.5 & 12 & 0.115385 & 0.865385 & 0.023077 \tabularnewline
[105,110[ & 107.5 & 5 & 0.048077 & 0.913462 & 0.009615 \tabularnewline
[110,115] & 112.5 & 9 & 0.086538 & 1 & 0.017308 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=247370&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]6[/C][C]0.057692[/C][C]0.057692[/C][C]0.011538[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]5[/C][C]0.048077[/C][C]0.105769[/C][C]0.009615[/C][/ROW]
[ROW][C][80,85[[/C][C]82.5[/C][C]9[/C][C]0.086538[/C][C]0.192308[/C][C]0.017308[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]19[/C][C]0.182692[/C][C]0.375[/C][C]0.036538[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]20[/C][C]0.192308[/C][C]0.567308[/C][C]0.038462[/C][/ROW]
[ROW][C][95,100[[/C][C]97.5[/C][C]19[/C][C]0.182692[/C][C]0.75[/C][C]0.036538[/C][/ROW]
[ROW][C][100,105[[/C][C]102.5[/C][C]12[/C][C]0.115385[/C][C]0.865385[/C][C]0.023077[/C][/ROW]
[ROW][C][105,110[[/C][C]107.5[/C][C]5[/C][C]0.048077[/C][C]0.913462[/C][C]0.009615[/C][/ROW]
[ROW][C][110,115][/C][C]112.5[/C][C]9[/C][C]0.086538[/C][C]1[/C][C]0.017308[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=247370&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=247370&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
[70,75[72.560.0576920.0576920.011538
[75,80[77.550.0480770.1057690.009615
[80,85[82.590.0865380.1923080.017308
[85,90[87.5190.1826920.3750.036538
[90,95[92.5200.1923080.5673080.038462
[95,100[97.5190.1826920.750.036538
[100,105[102.5120.1153850.8653850.023077
[105,110[107.550.0480770.9134620.009615
[110,115]112.590.08653810.017308


Figures (Output of Computation)

Input Parameters & R Code

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):
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')
}