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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 computationSun, 26 Oct 2014 19:44:37 +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/26/t1414352698q6lyd17pttjwskp.htm/, Retrieved Sun, 12 May 2024 18:01:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=246730, Retrieved Sun, 12 May 2024 18:01:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact65

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]
- RM D          [Boxplot and Trimmed Means] [Age 10 Data] [2014-10-26 19:39:35] [0af727c7d6fddd5894090204e2de4756]
- RMPD              [Histogram] [WJ10AVA Histogram] [2014-10-26 19:44:37] [892fd876d1e57c7e7407bd9e84fe5104] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
95
92
95
97
92
104
79
78
79
86
92
78
86
71
90
93
80
90
77
86
89
88
86
97
81
88
82
82
100
91
111
102
105
92
100
82
91
71
71
89
82
105
71
91
105
82
86
72
98
80
84
109
80
112
86
112
90
96
84
94
112
81
105
77
105
112
91
92
72
100
103
89
86
112
71
73
99
85
80
88
95
86
92
96
71
88
98
108
103
81
96
112
95
92
103
95
94
79
91
87
82
97
92
112

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=246730&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=246730&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=246730&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 time1 seconds
R Server'George Udny Yule' @ yule.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[70,75[72.590.0865380.0865380.017308
[75,80[77.570.0673080.1538460.013462
[80,85[82.5150.1442310.2980770.028846
[85,90[87.5170.1634620.4615380.032692
[90,95[92.5190.1826920.6442310.036538
[95,100[97.5140.1346150.7788460.026923
[100,105[102.580.0769230.8557690.015385
[105,110[107.570.0673080.9230770.013462
[110,115]112.580.07692310.015385

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[70,75[ & 72.5 & 9 & 0.086538 & 0.086538 & 0.017308 \tabularnewline
[75,80[ & 77.5 & 7 & 0.067308 & 0.153846 & 0.013462 \tabularnewline
[80,85[ & 82.5 & 15 & 0.144231 & 0.298077 & 0.028846 \tabularnewline
[85,90[ & 87.5 & 17 & 0.163462 & 0.461538 & 0.032692 \tabularnewline
[90,95[ & 92.5 & 19 & 0.182692 & 0.644231 & 0.036538 \tabularnewline
[95,100[ & 97.5 & 14 & 0.134615 & 0.778846 & 0.026923 \tabularnewline
[100,105[ & 102.5 & 8 & 0.076923 & 0.855769 & 0.015385 \tabularnewline
[105,110[ & 107.5 & 7 & 0.067308 & 0.923077 & 0.013462 \tabularnewline
[110,115] & 112.5 & 8 & 0.076923 & 1 & 0.015385 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=246730&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]9[/C][C]0.086538[/C][C]0.086538[/C][C]0.017308[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]7[/C][C]0.067308[/C][C]0.153846[/C][C]0.013462[/C][/ROW]
[ROW][C][80,85[[/C][C]82.5[/C][C]15[/C][C]0.144231[/C][C]0.298077[/C][C]0.028846[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]17[/C][C]0.163462[/C][C]0.461538[/C][C]0.032692[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]19[/C][C]0.182692[/C][C]0.644231[/C][C]0.036538[/C][/ROW]
[ROW][C][95,100[[/C][C]97.5[/C][C]14[/C][C]0.134615[/C][C]0.778846[/C][C]0.026923[/C][/ROW]
[ROW][C][100,105[[/C][C]102.5[/C][C]8[/C][C]0.076923[/C][C]0.855769[/C][C]0.015385[/C][/ROW]
[ROW][C][105,110[[/C][C]107.5[/C][C]7[/C][C]0.067308[/C][C]0.923077[/C][C]0.013462[/C][/ROW]
[ROW][C][110,115][/C][C]112.5[/C][C]8[/C][C]0.076923[/C][C]1[/C][C]0.015385[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=246730&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=246730&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[72.590.0865380.0865380.017308
[75,80[77.570.0673080.1538460.013462
[80,85[82.5150.1442310.2980770.028846
[85,90[87.5170.1634620.4615380.032692
[90,95[92.5190.1826920.6442310.036538
[95,100[97.5140.1346150.7788460.026923
[100,105[102.580.0769230.8557690.015385
[105,110[107.570.0673080.9230770.013462
[110,115]112.580.07692310.015385


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')
}