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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 27 Sep 2016 12:33:57 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Sep/27/t1474976053h8z6zv0ealfle34.htm/, Retrieved Wed, 08 May 2024 22:48:46 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Wed, 08 May 2024 22:48:46 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
70	
65	
62	
58	
55	
67	
64	
60	
71	
71	
73	
69	
81	
84	
84	
80	
76	
87	
83	
78	
87	
85	
81	
78	
87	
89	
88	
84	
82	
91	
93	
90	
100	
98	
95	
89	
99	
100	
99	
94	
86	
90	
86	
82	
86	
84	
82	
80	
86	
80	
79	
78	
73	
80	
79	
74	
82	
81	
76	
69

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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'Gwilym Jenkins' @ jenkins.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[55,60[57.520.0333330.0333330.006667
[60,65[62.530.050.0833330.01
[65,70[67.540.0666670.150.013333
[70,75[72.560.10.250.02
[75,80[77.570.1166670.3666670.023333
[80,85[82.5160.2666670.6333330.053333
[85,90[87.5110.1833330.8166670.036667
[90,95[92.550.0833330.90.016667
[95,100]97.560.110.02

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[55,60[ & 57.5 & 2 & 0.033333 & 0.033333 & 0.006667 \tabularnewline
[60,65[ & 62.5 & 3 & 0.05 & 0.083333 & 0.01 \tabularnewline
[65,70[ & 67.5 & 4 & 0.066667 & 0.15 & 0.013333 \tabularnewline
[70,75[ & 72.5 & 6 & 0.1 & 0.25 & 0.02 \tabularnewline
[75,80[ & 77.5 & 7 & 0.116667 & 0.366667 & 0.023333 \tabularnewline
[80,85[ & 82.5 & 16 & 0.266667 & 0.633333 & 0.053333 \tabularnewline
[85,90[ & 87.5 & 11 & 0.183333 & 0.816667 & 0.036667 \tabularnewline
[90,95[ & 92.5 & 5 & 0.083333 & 0.9 & 0.016667 \tabularnewline
[95,100] & 97.5 & 6 & 0.1 & 1 & 0.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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][55,60[[/C][C]57.5[/C][C]2[/C][C]0.033333[/C][C]0.033333[/C][C]0.006667[/C][/ROW]
[ROW][C][60,65[[/C][C]62.5[/C][C]3[/C][C]0.05[/C][C]0.083333[/C][C]0.01[/C][/ROW]
[ROW][C][65,70[[/C][C]67.5[/C][C]4[/C][C]0.066667[/C][C]0.15[/C][C]0.013333[/C][/ROW]
[ROW][C][70,75[[/C][C]72.5[/C][C]6[/C][C]0.1[/C][C]0.25[/C][C]0.02[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]7[/C][C]0.116667[/C][C]0.366667[/C][C]0.023333[/C][/ROW]
[ROW][C][80,85[[/C][C]82.5[/C][C]16[/C][C]0.266667[/C][C]0.633333[/C][C]0.053333[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]11[/C][C]0.183333[/C][C]0.816667[/C][C]0.036667[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]5[/C][C]0.083333[/C][C]0.9[/C][C]0.016667[/C][/ROW]
[ROW][C][95,100][/C][C]97.5[/C][C]6[/C][C]0.1[/C][C]1[/C][C]0.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
[55,60[57.520.0333330.0333330.006667
[60,65[62.530.050.0833330.01
[65,70[67.540.0666670.150.013333
[70,75[72.560.10.250.02
[75,80[77.570.1166670.3666670.023333
[80,85[82.5160.2666670.6333330.053333
[85,90[87.5110.1833330.8166670.036667
[90,95[92.550.0833330.90.016667
[95,100]97.560.110.02


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):
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 {
barplot(mytab <- sort(table(x),T),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')
}