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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 19:58:23 +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/t1414353542p8495bimvdsk26s.htm/, Retrieved Mon, 13 May 2024 03:02:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=246739, Retrieved Mon, 13 May 2024 03:02:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact76

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] [WJ10AKN Histogram] [2014-10-26 19:58:23] [892fd876d1e57c7e7407bd9e84fe5104] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
84
97
88
87
92
91
80
73
73
77
86
82
82
73
99
90
78
100
73
95
93
91
81
98
88
90
85
79
107
82
98
84
99
89
105
94
92
81
NA
86
90
101
73
88
90
84
89
73
98
82
77
107
84
93
96
107
95
89
82
92
100
75
94
83
92
102
98
94
83
107
107
91
83
100
77
74
92
100
92
93
89
86
97
82
73
93
97
93
89
86
89
107
90
104
96
93
104
83
92
83
83
96
84
107

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'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=246739&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=246739&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=246739&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'Sir Maurice George Kendall' @ kendall.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[70,75[72.580.0769230.0769230.015534
[75,80[77.560.0576920.1346150.01165
[80,85[82.5200.1923080.3269230.038835
[85,90[87.5150.1442310.4711540.029126
[90,95[92.5240.2307690.7019230.046602
[95,100[97.5140.1346150.8365380.027184
[100,105[102.580.0769230.9134620.015534
[105,110]107.580.0769230.9903850.015534

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[70,75[ & 72.5 & 8 & 0.076923 & 0.076923 & 0.015534 \tabularnewline
[75,80[ & 77.5 & 6 & 0.057692 & 0.134615 & 0.01165 \tabularnewline
[80,85[ & 82.5 & 20 & 0.192308 & 0.326923 & 0.038835 \tabularnewline
[85,90[ & 87.5 & 15 & 0.144231 & 0.471154 & 0.029126 \tabularnewline
[90,95[ & 92.5 & 24 & 0.230769 & 0.701923 & 0.046602 \tabularnewline
[95,100[ & 97.5 & 14 & 0.134615 & 0.836538 & 0.027184 \tabularnewline
[100,105[ & 102.5 & 8 & 0.076923 & 0.913462 & 0.015534 \tabularnewline
[105,110] & 107.5 & 8 & 0.076923 & 0.990385 & 0.015534 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=246739&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]8[/C][C]0.076923[/C][C]0.076923[/C][C]0.015534[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]6[/C][C]0.057692[/C][C]0.134615[/C][C]0.01165[/C][/ROW]
[ROW][C][80,85[[/C][C]82.5[/C][C]20[/C][C]0.192308[/C][C]0.326923[/C][C]0.038835[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]15[/C][C]0.144231[/C][C]0.471154[/C][C]0.029126[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]24[/C][C]0.230769[/C][C]0.701923[/C][C]0.046602[/C][/ROW]
[ROW][C][95,100[[/C][C]97.5[/C][C]14[/C][C]0.134615[/C][C]0.836538[/C][C]0.027184[/C][/ROW]
[ROW][C][100,105[[/C][C]102.5[/C][C]8[/C][C]0.076923[/C][C]0.913462[/C][C]0.015534[/C][/ROW]
[ROW][C][105,110][/C][C]107.5[/C][C]8[/C][C]0.076923[/C][C]0.990385[/C][C]0.015534[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=246739&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=246739&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[72.580.0769230.0769230.015534
[75,80[77.560.0576920.1346150.01165
[80,85[82.5200.1923080.3269230.038835
[85,90[87.5150.1442310.4711540.029126
[90,95[92.5240.2307690.7019230.046602
[95,100[97.5140.1346150.8365380.027184
[100,105[102.580.0769230.9134620.015534
[105,110]107.580.0769230.9903850.015534


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')
}