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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, 08 Feb 2011 14:43:41 +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/2011/Feb/08/t12971761347mkcy25g8qvnnm5.htm/, Retrieved Sun, 19 May 2024 11:12:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=118125, Retrieved Sun, 19 May 2024 11:12:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsgoudkoers, IKO, frequentietabel
Estimated Impact222

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [frequentietabel g...] [2011-02-08 14:43:41] [d41d8cd98f00b204e9800998ecf8427e] [Current]
- R       [Histogram] [] [2011-02-17 16:53:24] [81cdd92b187c11fcf96d69ee16e5a9b7]
-   P       [Histogram] [] [2011-02-17 16:59:21] [81cdd92b187c11fcf96d69ee16e5a9b7]
- RMP       [Kernel Density Estimation] [] [2011-02-17 17:08:31] [81cdd92b187c11fcf96d69ee16e5a9b7]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
30790
30800
31025
30835
31110
31270
31090
30755
31460
32135
32680
32700
32515
32275
32200
31835
31985
31875
31795
32260
33255
33160
32195
33130
33950
34210
33855
33735
34175
34265
33915
33660
33720
33810
33590
33545
33660
33165
33800
33880
33975
33930
33905
33890
33640
34395
34245
33940
34295
33745
33535
33715
33600
34120
34330
34130
33755
32910
32910
32850
32780
32565
31905
31975
31380
31355
31440
30310
31410
31300
31070
31075
31815

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'Herman Ole Andreas Wold' @ www.yougetit.org

\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 & 'Herman Ole Andreas Wold' @ www.yougetit.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=118125&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]'Herman Ole Andreas Wold' @ www.yougetit.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=118125&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=118125&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'Herman Ole Andreas Wold' @ www.yougetit.org






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[30000,30500[3025010.0136990.0136992.7e-05
[30500,31000[3075040.0547950.0684930.00011
[31000,31500[31250120.1643840.2328770.000329
[31500,32000[3175070.095890.3287670.000192
[32000,32500[3225050.0684930.397260.000137
[32500,33000[3275080.1095890.5068490.000219
[33000,33500[3325040.0547950.5616440.00011
[33500,34000[33750230.3150680.8767120.00063
[34000,34500]3425090.12328810.000247

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[30000,30500[ & 30250 & 1 & 0.013699 & 0.013699 & 2.7e-05 \tabularnewline
[30500,31000[ & 30750 & 4 & 0.054795 & 0.068493 & 0.00011 \tabularnewline
[31000,31500[ & 31250 & 12 & 0.164384 & 0.232877 & 0.000329 \tabularnewline
[31500,32000[ & 31750 & 7 & 0.09589 & 0.328767 & 0.000192 \tabularnewline
[32000,32500[ & 32250 & 5 & 0.068493 & 0.39726 & 0.000137 \tabularnewline
[32500,33000[ & 32750 & 8 & 0.109589 & 0.506849 & 0.000219 \tabularnewline
[33000,33500[ & 33250 & 4 & 0.054795 & 0.561644 & 0.00011 \tabularnewline
[33500,34000[ & 33750 & 23 & 0.315068 & 0.876712 & 0.00063 \tabularnewline
[34000,34500] & 34250 & 9 & 0.123288 & 1 & 0.000247 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=118125&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][30000,30500[[/C][C]30250[/C][C]1[/C][C]0.013699[/C][C]0.013699[/C][C]2.7e-05[/C][/ROW]
[ROW][C][30500,31000[[/C][C]30750[/C][C]4[/C][C]0.054795[/C][C]0.068493[/C][C]0.00011[/C][/ROW]
[ROW][C][31000,31500[[/C][C]31250[/C][C]12[/C][C]0.164384[/C][C]0.232877[/C][C]0.000329[/C][/ROW]
[ROW][C][31500,32000[[/C][C]31750[/C][C]7[/C][C]0.09589[/C][C]0.328767[/C][C]0.000192[/C][/ROW]
[ROW][C][32000,32500[[/C][C]32250[/C][C]5[/C][C]0.068493[/C][C]0.39726[/C][C]0.000137[/C][/ROW]
[ROW][C][32500,33000[[/C][C]32750[/C][C]8[/C][C]0.109589[/C][C]0.506849[/C][C]0.000219[/C][/ROW]
[ROW][C][33000,33500[[/C][C]33250[/C][C]4[/C][C]0.054795[/C][C]0.561644[/C][C]0.00011[/C][/ROW]
[ROW][C][33500,34000[[/C][C]33750[/C][C]23[/C][C]0.315068[/C][C]0.876712[/C][C]0.00063[/C][/ROW]
[ROW][C][34000,34500][/C][C]34250[/C][C]9[/C][C]0.123288[/C][C]1[/C][C]0.000247[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=118125&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=118125&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
[30000,30500[3025010.0136990.0136992.7e-05
[30500,31000[3075040.0547950.0684930.00011
[31000,31500[31250120.1643840.2328770.000329
[31500,32000[3175070.095890.3287670.000192
[32000,32500[3225050.0684930.397260.000137
[32500,33000[3275080.1095890.5068490.000219
[33000,33500[3325040.0547950.5616440.00011
[33500,34000[33750230.3150680.8767120.00063
[34000,34500]3425090.12328810.000247


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par2 = grey ; par3 = FALSE ; par4 = Interval/Ratio ;
Parameters (R input):
par1 = ; par2 = grey ; par3 = FALSE ; par4 = Interval/Ratio ;
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')
}