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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 computationFri, 04 Dec 2015 12:06:11 +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/2015/Dec/04/t14492308121qxxekl3a7qrcx5.htm/, Retrieved Thu, 16 May 2024 17:23:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=285089, Retrieved Thu, 16 May 2024 17:23:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2015-12-04 12:06:11] [8a291cd76385ab0c9561b5c1cbdd9681] [Current]
- R P     [Histogram] [Histogram weektotaal] [2015-12-04 12:10:43] [3ebd4d014a1334f70a4e3266a1ca8537]
- R P     [Histogram] [] [2015-12-04 12:23:36] [3ebd4d014a1334f70a4e3266a1ca8537]
- R P     [Histogram] [] [2015-12-04 12:23:36] [3ebd4d014a1334f70a4e3266a1ca8537]
- RMP     [Mean versus Median] [] [2015-12-04 12:36:17] [3ebd4d014a1334f70a4e3266a1ca8537]
- RMP     [Mean versus Median] [] [2015-12-04 12:46:23] [3ebd4d014a1334f70a4e3266a1ca8537]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4.2
0.5
4.6
5.2
2.7
4.2
1.8
1.7
3.8
0
3.9
3.5
1
1.7
7.8
4.9
3.8
0
7.7
0
7.7
0
10.1
1.7
0
8.6
3.9
4.2
1.7
0
7
1.8
8.4
3.4
7
3.9
2.7
7.7
1.7
1.7
11
1.8
2.1
0.7
1.7
10.5
6.2
1.8
1.7
7
3.5
3.8
0.5
1.8
8.4
7.7
1.7
4.9
0
1.8
6.3
5.2
1
1
0
5.6
5.6
3.8
3.5
6.3
0
5.9
1.7
3.5
1.8
0
8.4
5.1
7
3.4
4.2
0
1.4
3.9
6.3
7
2.1
4.5
0
3.5
8.1
4.2
0
1.7
5.3
1.8
0
13.6
9.4
0
2.1
1.7
2.1
0
3.5
1.8
0
8
0
2.1
3.9
1
7.7
2.1
1.7
0
1
6
0
1.8
3.5
4.2
7.6
1
1.8
2.1
1
1.7
8.4
10.8
1.8
2.1
0
0.7
5.6
6
1.7
1.8
5.2
6.3
0
3.4
1
1
5.6
8.3
2.6
2.1
0
3.5
8.3
7
3.4
1
4.2

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=285089&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=285089&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285089&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
[0,2[1660.4258060.4258060.212903
[2,4[3330.2129030.638710.106452
[4,6[5210.1354840.7741940.067742
[6,8[7200.1290320.9032260.064516
[8,10[9100.0645160.9677420.032258
[10,12[1140.0258060.9935480.012903
[12,14]1310.00645210.003226

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,2[ & 1 & 66 & 0.425806 & 0.425806 & 0.212903 \tabularnewline
[2,4[ & 3 & 33 & 0.212903 & 0.63871 & 0.106452 \tabularnewline
[4,6[ & 5 & 21 & 0.135484 & 0.774194 & 0.067742 \tabularnewline
[6,8[ & 7 & 20 & 0.129032 & 0.903226 & 0.064516 \tabularnewline
[8,10[ & 9 & 10 & 0.064516 & 0.967742 & 0.032258 \tabularnewline
[10,12[ & 11 & 4 & 0.025806 & 0.993548 & 0.012903 \tabularnewline
[12,14] & 13 & 1 & 0.006452 & 1 & 0.003226 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285089&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][0,2[[/C][C]1[/C][C]66[/C][C]0.425806[/C][C]0.425806[/C][C]0.212903[/C][/ROW]
[ROW][C][2,4[[/C][C]3[/C][C]33[/C][C]0.212903[/C][C]0.63871[/C][C]0.106452[/C][/ROW]
[ROW][C][4,6[[/C][C]5[/C][C]21[/C][C]0.135484[/C][C]0.774194[/C][C]0.067742[/C][/ROW]
[ROW][C][6,8[[/C][C]7[/C][C]20[/C][C]0.129032[/C][C]0.903226[/C][C]0.064516[/C][/ROW]
[ROW][C][8,10[[/C][C]9[/C][C]10[/C][C]0.064516[/C][C]0.967742[/C][C]0.032258[/C][/ROW]
[ROW][C][10,12[[/C][C]11[/C][C]4[/C][C]0.025806[/C][C]0.993548[/C][C]0.012903[/C][/ROW]
[ROW][C][12,14][/C][C]13[/C][C]1[/C][C]0.006452[/C][C]1[/C][C]0.003226[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285089&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285089&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
[0,2[1660.4258060.4258060.212903
[2,4[3330.2129030.638710.106452
[4,6[5210.1354840.7741940.067742
[6,8[7200.1290320.9032260.064516
[8,10[9100.0645160.9677420.032258
[10,12[1140.0258060.9935480.012903
[12,14]1310.00645210.003226


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 {
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')
}