Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 16 Feb 2016 19:07:33 +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/2016/Feb/16/t1455649724rr5dtuj1w0c7sj5.htm/, Retrieved Mon, 06 May 2024 02:48:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=292054, Retrieved Mon, 06 May 2024 02:48:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [] [2016-02-04 09:16:54] [e56dfe8be31eb19d2e02d76fcb74f554]
- R PD    [Histogram] [] [2016-02-16 19:07:33] [c0f67b4e93ea0adf92c2b9d3976edd70] [Current]
-   P       [Histogram] [] [2016-02-16 19:10:21] [e56dfe8be31eb19d2e02d76fcb74f554]
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Dataseries X:
87.5
87.3
87.8
88.1
88.0
87.8
87.0
87.2
87.0
89.4
89.1
87.8
87.8
88.0
86.5
84.1
84.3
84.7
85.7
86.4
86.0
86.9
89.1
90.7
89.8
89.4
88.6
86.8
86.8
89.5
88.5
91.2
92.3
92.0
92.8
92.9
92.7
94.2
94.0
94.3
94.8
94.7
95.1
97.0
97.9
97.3
96.5
98.1
99.3
99.9
99.9
99.9
99.8
99.5
99.9
100.1
100.1
100.2
100.6
100.8
100.8
100.5
101.0
100.5
99.0
97.9
97.6
97.2
96.5
96.3
96.3
96.2
95.6
93.5
93.2
93.6
94.6
96.1
98.4
99.6
99.4
99.7
100.1
99.9




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=292054&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=292054&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292054&T=0

As an alternative you can also use a 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
[80,85[82.530.0357140.0357140.007143
[85,90[87.5270.3214290.3571430.064286
[90,95[92.5160.1904760.5476190.038095
[95,100[97.5280.3333330.8809520.066667
[100,105]102.5100.11904810.02381

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[80,85[ & 82.5 & 3 & 0.035714 & 0.035714 & 0.007143 \tabularnewline
[85,90[ & 87.5 & 27 & 0.321429 & 0.357143 & 0.064286 \tabularnewline
[90,95[ & 92.5 & 16 & 0.190476 & 0.547619 & 0.038095 \tabularnewline
[95,100[ & 97.5 & 28 & 0.333333 & 0.880952 & 0.066667 \tabularnewline
[100,105] & 102.5 & 10 & 0.119048 & 1 & 0.02381 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=292054&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][80,85[[/C][C]82.5[/C][C]3[/C][C]0.035714[/C][C]0.035714[/C][C]0.007143[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]27[/C][C]0.321429[/C][C]0.357143[/C][C]0.064286[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]16[/C][C]0.190476[/C][C]0.547619[/C][C]0.038095[/C][/ROW]
[ROW][C][95,100[[/C][C]97.5[/C][C]28[/C][C]0.333333[/C][C]0.880952[/C][C]0.066667[/C][/ROW]
[ROW][C][100,105][/C][C]102.5[/C][C]10[/C][C]0.119048[/C][C]1[/C][C]0.02381[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=292054&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292054&T=1

As an alternative you can also use a QR Code:  

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

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[80,85[82.530.0357140.0357140.007143
[85,90[87.5270.3214290.3571430.064286
[90,95[92.5160.1904760.5476190.038095
[95,100[97.5280.3333330.8809520.066667
[100,105]102.5100.11904810.02381



Parameters (Session):
par1 = 3 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 3 ; 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 {
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')
}