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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 computationFri, 02 Oct 2015 20:52:19 +0100
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/Oct/02/t1443815609heyhgpr03jmufye.htm/, Retrieved Tue, 14 May 2024 08:54:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=281197, Retrieved Tue, 14 May 2024 08:54:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Frequentietabel-I...] [2015-10-02 19:52:19] [bcb0da8ff6be95621a49a67fe6a7b572] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2 754 542
2 899 512
2 928 886
3 011 252
2 932 895
3 069 307
2 863 923
2 585 491
2 993 900
3 023 542
2 491 370
2 341 705
2 126 472
2 196 705
2 368 313
2 285 174
2 163 877
2 299 241
2 275 643
2 163 091
2 416 149
2 434 553
2 281 937
2 440 464
2 255 745
2 389 872
2 863 148
2 623 516
2 558 136
2 898 129
2 537 720
2 543 469
2 779 739
2 884 779
2 711 624
2 817 771
2 884 477
3 058 996
3 285 298
2 879 617
3 220 416
3 144 280
2 940 811
2 986 507
3 153 720
2 995 806
2 990 242
2 879 837
2 848 699
3 138 385
3 532 447
3 121 872
3 309 250
3 215 022
2 966 778
3 010 284
3 083 824
3 257 727
3 180 374
3 036 414
2 966 714
3 067 677
3 339 789
3 299 861
3 193 328
3 181 266
3 193 356
2 898 282
2 929 524
3 217 311
3 126 249
3 131 083
3 008 058
2 868 318
3 207 495
3 109 336
3 070 725
2 989 963
3 287 552
2 835 238
3 368 961
3 291 689
3 008 536
2 974 109

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=281197&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=281197&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281197&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
[2e+06,2200000[210000040.0476190.0476190
[2200000,2400000[230000080.0952380.1428570
[2400000,2600000[250000080.0952380.2380950
[2600000,2800000[270000040.0476190.2857140
[2800000,3e+06[2900000250.2976190.5833331e-06
[3e+06,3200000[3100000220.2619050.8452381e-06
[3200000,3400000[3300000120.1428570.9880951e-06
[3400000,3600000]350000010.01190510

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[2e+06,2200000[ & 2100000 & 4 & 0.047619 & 0.047619 & 0 \tabularnewline
[2200000,2400000[ & 2300000 & 8 & 0.095238 & 0.142857 & 0 \tabularnewline
[2400000,2600000[ & 2500000 & 8 & 0.095238 & 0.238095 & 0 \tabularnewline
[2600000,2800000[ & 2700000 & 4 & 0.047619 & 0.285714 & 0 \tabularnewline
[2800000,3e+06[ & 2900000 & 25 & 0.297619 & 0.583333 & 1e-06 \tabularnewline
[3e+06,3200000[ & 3100000 & 22 & 0.261905 & 0.845238 & 1e-06 \tabularnewline
[3200000,3400000[ & 3300000 & 12 & 0.142857 & 0.988095 & 1e-06 \tabularnewline
[3400000,3600000] & 3500000 & 1 & 0.011905 & 1 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281197&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][2e+06,2200000[[/C][C]2100000[/C][C]4[/C][C]0.047619[/C][C]0.047619[/C][C]0[/C][/ROW]
[ROW][C][2200000,2400000[[/C][C]2300000[/C][C]8[/C][C]0.095238[/C][C]0.142857[/C][C]0[/C][/ROW]
[ROW][C][2400000,2600000[[/C][C]2500000[/C][C]8[/C][C]0.095238[/C][C]0.238095[/C][C]0[/C][/ROW]
[ROW][C][2600000,2800000[[/C][C]2700000[/C][C]4[/C][C]0.047619[/C][C]0.285714[/C][C]0[/C][/ROW]
[ROW][C][2800000,3e+06[[/C][C]2900000[/C][C]25[/C][C]0.297619[/C][C]0.583333[/C][C]1e-06[/C][/ROW]
[ROW][C][3e+06,3200000[[/C][C]3100000[/C][C]22[/C][C]0.261905[/C][C]0.845238[/C][C]1e-06[/C][/ROW]
[ROW][C][3200000,3400000[[/C][C]3300000[/C][C]12[/C][C]0.142857[/C][C]0.988095[/C][C]1e-06[/C][/ROW]
[ROW][C][3400000,3600000][/C][C]3500000[/C][C]1[/C][C]0.011905[/C][C]1[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281197&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281197&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
[2e+06,2200000[210000040.0476190.0476190
[2200000,2400000[230000080.0952380.1428570
[2400000,2600000[250000080.0952380.2380950
[2600000,2800000[270000040.0476190.2857140
[2800000,3e+06[2900000250.2976190.5833331e-06
[3e+06,3200000[3100000220.2619050.8452381e-06
[3200000,3400000[3300000120.1428570.9880951e-06
[3400000,3600000]350000010.01190510


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')
}