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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, 03 Aug 2017 15:13:41 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Aug/03/t15017660642lc5cqqosurjhjt.htm/, Retrieved Fri, 10 May 2024 03:53:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306878, Retrieved Fri, 10 May 2024 03:53:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2017-08-03 13:13:41] [eec775fda337aa2da775a098928b5865] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3469648
3456726
3443622
3416504
3684772
3670576
3469648
3336060
3348982
3348982
3363360
3389204
3429426
3429426
3403582
3336060
3684772
3737916
3657654
3469648
3550092
3429426
3483844
3509870
3536988
3469648
3483844
3389204
3684772
3778138
3697876
3550092
3710798
3536988
3697876
3684772
3724994
3577210
3737916
3724994
3966144
3911726
3697876
3590132
3737916
3536988
3684772
3710798
3765216
3644732
3710798
3751020
3898804
3778138
3617432
3443622
3604510
3162250
3376282
3496766
3617432
3443622
3443622
3443622
3536988
3403582
3228498
3081988
3188276
2773316
3027570
3175354
3202472
3054688
3067610
3027570
3162250
3067610
2881060
2746198
2974244
2479022
2800616
2947126
2947126
2773316
2612610
2599688
2746198
2612610
2358538
2183454
2371460
1929382
2331238
2545088
2612610
2464826
2278094
2411682
2464826
2424604
2022566
1836016
1969422
1567566
1982526
2130310
2250794
2049866
1861860
1969422
2022566
1916278
1514422
1339338
1500044
1057966
1540266
1836016

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306878&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=306878&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306878&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[1000000,1500000[125000020.0166670.0166670
[1500000,2000000[1750000120.10.1166670
[2000000,2500000[2250000150.1250.2416670
[2500000,3000000[2750000140.1166670.3583330
[3000000,3500000[3250000390.3250.6833331e-06
[3500000,4000000]3750000380.31666711e-06

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[1000000,1500000[ & 1250000 & 2 & 0.016667 & 0.016667 & 0 \tabularnewline
[1500000,2000000[ & 1750000 & 12 & 0.1 & 0.116667 & 0 \tabularnewline
[2000000,2500000[ & 2250000 & 15 & 0.125 & 0.241667 & 0 \tabularnewline
[2500000,3000000[ & 2750000 & 14 & 0.116667 & 0.358333 & 0 \tabularnewline
[3000000,3500000[ & 3250000 & 39 & 0.325 & 0.683333 & 1e-06 \tabularnewline
[3500000,4000000] & 3750000 & 38 & 0.316667 & 1 & 1e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306878&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][1000000,1500000[[/C][C]1250000[/C][C]2[/C][C]0.016667[/C][C]0.016667[/C][C]0[/C][/ROW]
[ROW][C][1500000,2000000[[/C][C]1750000[/C][C]12[/C][C]0.1[/C][C]0.116667[/C][C]0[/C][/ROW]
[ROW][C][2000000,2500000[[/C][C]2250000[/C][C]15[/C][C]0.125[/C][C]0.241667[/C][C]0[/C][/ROW]
[ROW][C][2500000,3000000[[/C][C]2750000[/C][C]14[/C][C]0.116667[/C][C]0.358333[/C][C]0[/C][/ROW]
[ROW][C][3000000,3500000[[/C][C]3250000[/C][C]39[/C][C]0.325[/C][C]0.683333[/C][C]1e-06[/C][/ROW]
[ROW][C][3500000,4000000][/C][C]3750000[/C][C]38[/C][C]0.316667[/C][C]1[/C][C]1e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306878&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306878&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
[1000000,1500000[125000020.0166670.0166670
[1500000,2000000[1750000120.10.1166670
[2000000,2500000[2250000150.1250.2416670
[2500000,3000000[2750000140.1166670.3583330
[3000000,3500000[3250000390.3250.6833331e-06
[3500000,4000000]3750000380.31666711e-06


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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,'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')
}