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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, 16 Aug 2015 14:38:46 +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/Aug/16/t14397323420tgido2pso9e5dm.htm/, Retrieved Sun, 19 May 2024 12:59:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=280136, Retrieved Sun, 19 May 2024 12:59:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2015-08-16 13:38:46] [f898ec974b62c60a8bec4044c4c271e3] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1 544 400
1 487 200
1 573 000
1 258 400
1 630 200
1 601 600
1 716 000
1 773 200
1 973 400
1 716 000
1 630 200
2 030 600
1 716 000
1 287 000
1 515 800
1 144 000
1 601 600
1 315 600
1 744 600
1 573 000
1 658 800
1 859 000
1 830 400
2 173 600
1 573 000
1 315 600
1 458 600
1 058 200
1 515 800
1 172 600
1 658 800
1 573 000
1 401 400
2 002 000
1 801 800
2 059 200
1 544 400
1 430 000
1 287 000
1 058 200
1 401 400
1 258 400
1 716 000
1 658 800
1 430 000
1 916 200
1 773 200
2 288 000
1 830 400
1 115 400
1 115 400
1 115 400
1 315 600
1 315 600
1 773 200
1 630 200
1 458 600
1 830 400
1 687 400
2 431 000
1 916 200
1 115 400
1 172 600
972 400
1 344 200
1 544 400
1 944 800
1 916 200
1 544 400
1 801 800
1 601 600
2 288 000
1 744 600
1 401 400
1 258 400
943 800
1 401 400
1 687 400
1 973 400
1 859 000
1 372 800
1 973 400
1 544 400
2 373 800
1 973 400
1 430 000
1 315 600
886 600
1 401 400
1 344 200
2 030 600
2 030 600
1 544 400
2 002 000
1 487 200
2 316 600
1 973 400
1 458 600
1 115 400
772 200
1 515 800
1 458 600
1 916 200
2 202 200
1 630 200
1 830 400
1 372 800
2 373 800

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280136&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280136&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280136&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'Gertrude Mary Cox' @ cox.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[6e+05,8e+05[7e+0510.0092590.0092590
[8e+05,1e+06[9e+0530.0277780.0370370
[1e+06,1200000[1100000100.0925930.129630
[1200000,1400000[1300000140.129630.2592591e-06
[1400000,1600000[1500000270.250.5092591e-06
[1600000,1800000[1700000210.1944440.7037041e-06
[1800000,2e+06[1900000180.1666670.870371e-06
[2e+06,2200000[210000070.0648150.9351850
[2200000,2400000[230000060.0555560.9907410
[2400000,2600000]250000010.00925910

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[6e+05,8e+05[ & 7e+05 & 1 & 0.009259 & 0.009259 & 0 \tabularnewline
[8e+05,1e+06[ & 9e+05 & 3 & 0.027778 & 0.037037 & 0 \tabularnewline
[1e+06,1200000[ & 1100000 & 10 & 0.092593 & 0.12963 & 0 \tabularnewline
[1200000,1400000[ & 1300000 & 14 & 0.12963 & 0.259259 & 1e-06 \tabularnewline
[1400000,1600000[ & 1500000 & 27 & 0.25 & 0.509259 & 1e-06 \tabularnewline
[1600000,1800000[ & 1700000 & 21 & 0.194444 & 0.703704 & 1e-06 \tabularnewline
[1800000,2e+06[ & 1900000 & 18 & 0.166667 & 0.87037 & 1e-06 \tabularnewline
[2e+06,2200000[ & 2100000 & 7 & 0.064815 & 0.935185 & 0 \tabularnewline
[2200000,2400000[ & 2300000 & 6 & 0.055556 & 0.990741 & 0 \tabularnewline
[2400000,2600000] & 2500000 & 1 & 0.009259 & 1 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280136&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][6e+05,8e+05[[/C][C]7e+05[/C][C]1[/C][C]0.009259[/C][C]0.009259[/C][C]0[/C][/ROW]
[ROW][C][8e+05,1e+06[[/C][C]9e+05[/C][C]3[/C][C]0.027778[/C][C]0.037037[/C][C]0[/C][/ROW]
[ROW][C][1e+06,1200000[[/C][C]1100000[/C][C]10[/C][C]0.092593[/C][C]0.12963[/C][C]0[/C][/ROW]
[ROW][C][1200000,1400000[[/C][C]1300000[/C][C]14[/C][C]0.12963[/C][C]0.259259[/C][C]1e-06[/C][/ROW]
[ROW][C][1400000,1600000[[/C][C]1500000[/C][C]27[/C][C]0.25[/C][C]0.509259[/C][C]1e-06[/C][/ROW]
[ROW][C][1600000,1800000[[/C][C]1700000[/C][C]21[/C][C]0.194444[/C][C]0.703704[/C][C]1e-06[/C][/ROW]
[ROW][C][1800000,2e+06[[/C][C]1900000[/C][C]18[/C][C]0.166667[/C][C]0.87037[/C][C]1e-06[/C][/ROW]
[ROW][C][2e+06,2200000[[/C][C]2100000[/C][C]7[/C][C]0.064815[/C][C]0.935185[/C][C]0[/C][/ROW]
[ROW][C][2200000,2400000[[/C][C]2300000[/C][C]6[/C][C]0.055556[/C][C]0.990741[/C][C]0[/C][/ROW]
[ROW][C][2400000,2600000][/C][C]2500000[/C][C]1[/C][C]0.009259[/C][C]1[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280136&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280136&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
[6e+05,8e+05[7e+0510.0092590.0092590
[8e+05,1e+06[9e+0530.0277780.0370370
[1e+06,1200000[1100000100.0925930.129630
[1200000,1400000[1300000140.129630.2592591e-06
[1400000,1600000[1500000270.250.5092591e-06
[1600000,1800000[1700000210.1944440.7037041e-06
[1800000,2e+06[1900000180.1666670.870371e-06
[2e+06,2200000[210000070.0648150.9351850
[2200000,2400000[230000060.0555560.9907410
[2400000,2600000]250000010.00925910


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 {
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')
}