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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationWed, 16 Nov 2016 13:59:05 +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/2016/Nov/16/t1479301169tzqq6fanwbplxt2.htm/, Retrieved Sat, 04 May 2024 23:06:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296765, Retrieved Sat, 04 May 2024 23:06:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [F1] [2016-11-16 12:59:05] [94ac3c9a028ddd47e8862e80eac9f626] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
295
520
550
610
775
885
965
475
875
1330
1635
920
1700
1465
1190
1390
1580
1775
1975
2440
2160
2670
3340
3230
2175
2035
3520
3945
2920
2495
2630
3610
5020
5755
7040
5345
4260
4785
3735
2980
2910

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296765&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]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=296765&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296765&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 time0 seconds
R ServerBig Analytics Cloud Computing Center






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,1000[500100.2439020.2439020.000244
[1000,2000[150090.2195120.4634150.00022
[2000,3000[2500100.2439020.7073170.000244
[3000,4000[350060.1463410.8536590.000146
[4000,5000[450020.048780.9024394.9e-05
[5000,6000[550030.0731710.975617.3e-05
[6000,7000[6500000.975610
[7000,8000]750010.0243912.4e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,1000[ & 500 & 10 & 0.243902 & 0.243902 & 0.000244 \tabularnewline
[1000,2000[ & 1500 & 9 & 0.219512 & 0.463415 & 0.00022 \tabularnewline
[2000,3000[ & 2500 & 10 & 0.243902 & 0.707317 & 0.000244 \tabularnewline
[3000,4000[ & 3500 & 6 & 0.146341 & 0.853659 & 0.000146 \tabularnewline
[4000,5000[ & 4500 & 2 & 0.04878 & 0.902439 & 4.9e-05 \tabularnewline
[5000,6000[ & 5500 & 3 & 0.073171 & 0.97561 & 7.3e-05 \tabularnewline
[6000,7000[ & 6500 & 0 & 0 & 0.97561 & 0 \tabularnewline
[7000,8000] & 7500 & 1 & 0.02439 & 1 & 2.4e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296765&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][0,1000[[/C][C]500[/C][C]10[/C][C]0.243902[/C][C]0.243902[/C][C]0.000244[/C][/ROW]
[ROW][C][1000,2000[[/C][C]1500[/C][C]9[/C][C]0.219512[/C][C]0.463415[/C][C]0.00022[/C][/ROW]
[ROW][C][2000,3000[[/C][C]2500[/C][C]10[/C][C]0.243902[/C][C]0.707317[/C][C]0.000244[/C][/ROW]
[ROW][C][3000,4000[[/C][C]3500[/C][C]6[/C][C]0.146341[/C][C]0.853659[/C][C]0.000146[/C][/ROW]
[ROW][C][4000,5000[[/C][C]4500[/C][C]2[/C][C]0.04878[/C][C]0.902439[/C][C]4.9e-05[/C][/ROW]
[ROW][C][5000,6000[[/C][C]5500[/C][C]3[/C][C]0.073171[/C][C]0.97561[/C][C]7.3e-05[/C][/ROW]
[ROW][C][6000,7000[[/C][C]6500[/C][C]0[/C][C]0[/C][C]0.97561[/C][C]0[/C][/ROW]
[ROW][C][7000,8000][/C][C]7500[/C][C]1[/C][C]0.02439[/C][C]1[/C][C]2.4e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296765&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296765&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
[0,1000[500100.2439020.2439020.000244
[1000,2000[150090.2195120.4634150.00022
[2000,3000[2500100.2439020.7073170.000244
[3000,4000[350060.1463410.8536590.000146
[4000,5000[450020.048780.9024394.9e-05
[5000,6000[550030.0731710.975617.3e-05
[6000,7000[6500000.975610
[7000,8000]750010.0243912.4e-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,'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')
}