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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 computationSun, 09 Feb 2014 12:27:35 -0500
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/Feb/09/t13919669344y4mrrn6saluqdj.htm/, Retrieved Thu, 16 May 2024 18:01:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=233456, Retrieved Thu, 16 May 2024 18:01:58 +0000
QR Codes:

Original text written by user:frequentietabel met 4 klassen
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact88

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [] [2014-02-09 14:44:34] [967af62594a7ddaeafac2725d7422db7]
- R P   [Histogram] [] [2014-02-09 16:30:42] [967af62594a7ddaeafac2725d7422db7]
-         [Histogram] [] [2014-02-09 16:44:22] [967af62594a7ddaeafac2725d7422db7]
- R PD      [Histogram] [] [2014-02-09 17:14:30] [967af62594a7ddaeafac2725d7422db7]
- R P           [Histogram] [] [2014-02-09 17:27:35] [a051cf513b3103c0fd2487dcb9eab576] [Current]
-   P             [Histogram] [] [2014-02-09 17:32:38] [967af62594a7ddaeafac2725d7422db7]
- RMP             [Kernel Density Estimation] [] [2014-02-09 17:43:08] [967af62594a7ddaeafac2725d7422db7]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1516
1289
1428
1335
1402
1475
1582
1317
1450
1497
1556
981
1807
1573
1756
1708
1737
1679
1872
1598
1747
1882
1369
865
1432
1172
1268
1120
1235
1272
1360
1069
1434
1552
1584
1070
1676
1690
1643
1446
1566
1352
1805
1613
1824
1866
1774
1505
1972
1856
2037
1888
2167
2191
2036
2103
2131
2039
1983
1629
2032
2216
2141
2073
2145
2429
2157
1994
2116
2287
2162
1699

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=233456&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]2 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=233456&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=233456&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[500,1000[75020.0277780.0277785.6e-05
[1000,1500[1250210.2916670.3194440.000583
[1500,2000[1750320.4444440.7638890.000889
[2000,2500]2250170.23611110.000472

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[500,1000[ & 750 & 2 & 0.027778 & 0.027778 & 5.6e-05 \tabularnewline
[1000,1500[ & 1250 & 21 & 0.291667 & 0.319444 & 0.000583 \tabularnewline
[1500,2000[ & 1750 & 32 & 0.444444 & 0.763889 & 0.000889 \tabularnewline
[2000,2500] & 2250 & 17 & 0.236111 & 1 & 0.000472 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=233456&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][500,1000[[/C][C]750[/C][C]2[/C][C]0.027778[/C][C]0.027778[/C][C]5.6e-05[/C][/ROW]
[ROW][C][1000,1500[[/C][C]1250[/C][C]21[/C][C]0.291667[/C][C]0.319444[/C][C]0.000583[/C][/ROW]
[ROW][C][1500,2000[[/C][C]1750[/C][C]32[/C][C]0.444444[/C][C]0.763889[/C][C]0.000889[/C][/ROW]
[ROW][C][2000,2500][/C][C]2250[/C][C]17[/C][C]0.236111[/C][C]1[/C][C]0.000472[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=233456&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=233456&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
[500,1000[75020.0277780.0277785.6e-05
[1000,1500[1250210.2916670.3194440.000583
[1500,2000[1750320.4444440.7638890.000889
[2000,2500]2250170.23611110.000472


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 4 ; 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')
}