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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 computationThu, 04 Feb 2016 16:20:35 +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/04/t1454602940zl9jsfl8nuwstwm.htm/, Retrieved Mon, 29 Apr 2024 23:42:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=291859, Retrieved Mon, 29 Apr 2024 23:42:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact170

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2016-02-04 16:20:35] [f824ea295e177f9d3dd7528a75f4b680] [Current]
-         [Histogram] [] [2016-02-18 13:06:55] [0fac179d48b12d87f452d447736804ac]
- R         [Histogram] [] [2016-02-23 10:49:45] [0fac179d48b12d87f452d447736804ac]
- R P       [Histogram] [] [2016-02-23 11:03:31] [0fac179d48b12d87f452d447736804ac]
- R P     [Histogram] [] [2016-02-18 13:10:17] [0fac179d48b12d87f452d447736804ac]
- RMP     [Kernel Density Estimation] [] [2016-02-18 13:18:17] [0fac179d48b12d87f452d447736804ac]
- R P       [Kernel Density Estimation] [] [2016-02-23 11:06:18] [0fac179d48b12d87f452d447736804ac]
- RMPD      [Quartiles] [] [2016-02-23 11:11:20] [0fac179d48b12d87f452d447736804ac]
- RMP       [Notched Boxplots] [] [2016-02-23 11:17:35] [0fac179d48b12d87f452d447736804ac]
- RMPD      [Notched Boxplots] [] [2016-02-23 11:34:06] [0fac179d48b12d87f452d447736804ac]
- RMP       [Quartiles] [] [2016-02-23 11:40:43] [0fac179d48b12d87f452d447736804ac]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4736
4840
4413
4571
4106
4801
3956
3829
4453
4027
4121
4798
3233
3554
3952
3951
3685
4312
3867
4140
4114
3818
3377
3453
3502
4017
5410
5184
5529
6434
4962
2980
2937
3023
2731
3163
3146
3173
3724
3224
4114
3450
2957
3882
4284
4181
3760
4457
4167
3962
5247
5157
3697
3514
3786
3297
3571
3871
3492
3051
3735
3645
4852
4232
3804
4464
4259
3373
4134
4488
3333
4772
4929
5555
7183
9266
4003
3051
3507
3273
3942
3216
3232
3593

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=291859&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]0 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=291859&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=291859&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 time0 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[2000,3000[250040.0476190.0476194.8e-05
[3000,4000[3500420.50.5476195e-04
[4000,5000[4500290.3452380.8928570.000345
[5000,6000[550060.0714290.9642867.1e-05
[6000,7000[650010.0119050.976191.2e-05
[7000,8000[750010.0119050.9880951.2e-05
[8000,9000[8500000.9880950
[9000,10000]950010.01190511.2e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[2000,3000[ & 2500 & 4 & 0.047619 & 0.047619 & 4.8e-05 \tabularnewline
[3000,4000[ & 3500 & 42 & 0.5 & 0.547619 & 5e-04 \tabularnewline
[4000,5000[ & 4500 & 29 & 0.345238 & 0.892857 & 0.000345 \tabularnewline
[5000,6000[ & 5500 & 6 & 0.071429 & 0.964286 & 7.1e-05 \tabularnewline
[6000,7000[ & 6500 & 1 & 0.011905 & 0.97619 & 1.2e-05 \tabularnewline
[7000,8000[ & 7500 & 1 & 0.011905 & 0.988095 & 1.2e-05 \tabularnewline
[8000,9000[ & 8500 & 0 & 0 & 0.988095 & 0 \tabularnewline
[9000,10000] & 9500 & 1 & 0.011905 & 1 & 1.2e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=291859&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][2000,3000[[/C][C]2500[/C][C]4[/C][C]0.047619[/C][C]0.047619[/C][C]4.8e-05[/C][/ROW]
[ROW][C][3000,4000[[/C][C]3500[/C][C]42[/C][C]0.5[/C][C]0.547619[/C][C]5e-04[/C][/ROW]
[ROW][C][4000,5000[[/C][C]4500[/C][C]29[/C][C]0.345238[/C][C]0.892857[/C][C]0.000345[/C][/ROW]
[ROW][C][5000,6000[[/C][C]5500[/C][C]6[/C][C]0.071429[/C][C]0.964286[/C][C]7.1e-05[/C][/ROW]
[ROW][C][6000,7000[[/C][C]6500[/C][C]1[/C][C]0.011905[/C][C]0.97619[/C][C]1.2e-05[/C][/ROW]
[ROW][C][7000,8000[[/C][C]7500[/C][C]1[/C][C]0.011905[/C][C]0.988095[/C][C]1.2e-05[/C][/ROW]
[ROW][C][8000,9000[[/C][C]8500[/C][C]0[/C][C]0[/C][C]0.988095[/C][C]0[/C][/ROW]
[ROW][C][9000,10000][/C][C]9500[/C][C]1[/C][C]0.011905[/C][C]1[/C][C]1.2e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=291859&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=291859&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
[2000,3000[250040.0476190.0476194.8e-05
[3000,4000[3500420.50.5476195e-04
[4000,5000[4500290.3452380.8928570.000345
[5000,6000[550060.0714290.9642867.1e-05
[6000,7000[650010.0119050.976191.2e-05
[7000,8000[750010.0119050.9880951.2e-05
[8000,9000[8500000.9880950
[9000,10000]950010.01190511.2e-05


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')
}