FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationFri, 28 Jul 2017 14:19:36 +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/Jul/28/t1501244416uff5q8lsk4wtv6v.htm/, Retrieved Thu, 16 May 2024 01:48:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306777, Retrieved Thu, 16 May 2024 01:48:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Histogram omzet J...] [2017-07-28 12:19:36] [41db9c2917eeaa94887144dd7479aea5] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
 4 213,144 
 4 197,453 
 4 181,541 
 4 148,612 
 4 474,366 
 4 457,128 
 4 213,144 
 4 050,930 
 4 066,621 
 4 066,621 
 4 084,080 
 4 115,462 
 4 164,303 
 4 164,303 
 4 132,921 
 4 050,930 
 4 474,366 
 4 538,898 
 4 441,437 
 4 213,144 
 4 310,826 
 4 164,303 
 4 230,382 
 4 261,985 
 4 294,914 
 4 213,144 
 4 230,382 
 4 115,462 
 4 474,366 
 4 587,739 
 4 490,278 
 4 310,826 
 4 505,969 
 4 294,914 
 4 490,278 
 4 474,366 
 4 523,207 
 4 343,755 
 4 538,898 
 4 523,207 
 4 816,032 
 4 749,953 
 4 490,278 
 4 359,446 
 4 538,898 
 4 294,914 
 4 474,366 
 4 505,969 
 4 572,048 
 4 425,746 
 4 505,969 
 4 554,810 
 4 734,262 
 4 587,739 
 4 392,596 
 4 181,541 
 4 376,905 
 3 839,875 
 4 099,771 
 4 246,073 
 4 392,596 
 4 181,541 
 4 181,541 
 4 181,541 
 4 294,914 
 4 132,921 
 3 920,319 
 3 742,414 
 3 871,478 
 3 367,598 
 3 676,335 
 3 855,787 
 3 888,716 
 3 709,264 
 3 724,955 
 3 676,335 
 3 839,875 
 3 724,955 
 3 498,430 
 3 334,669 
 3 611,582 
 3 010,241 
 3 400,748 
 3 578,653 
 3 578,653 
 3 367,598 
 3 172,455 
 3 156,764 
 3 334,669 
 3 172,455 
 2 863,939 
 2 651,337 
 2 879,630 
 2 342,821 
 2 830,789 
 3 090,464 
 3 172,455 
 2 993,003 
 2 766,257 
 2 928,471 
 2 993,003 
 2 944,162 
 2 455,973 
 2 229,448 
 2 391,441 
 1 903,473 
 2 407,353 
 2 586,805 
 2 733,107 
 2 489,123 
 2 260,830 
 2 391,441 
 2 455,973 
 2 326,909 
 1 838,941 
 1 626,339 
 1 821,482 
 1 284,673 
 1 870,323 
 2 229,448

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=306777&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=306777&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306777&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
[1000,1500[125010.0083330.0083331.7e-05
[1500,2000[175050.0416670.058.3e-05
[2000,2500[2250110.0916670.1416670.000183
[2500,3000[2750110.0916670.2333330.000183
[3000,3500[3250120.10.3333332e-04
[3500,4000[3750150.1250.4583330.00025
[4000,4500[4250500.4166670.8750.000833
[4500,5000]4750150.12510.00025

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[1000,1500[ & 1250 & 1 & 0.008333 & 0.008333 & 1.7e-05 \tabularnewline
[1500,2000[ & 1750 & 5 & 0.041667 & 0.05 & 8.3e-05 \tabularnewline
[2000,2500[ & 2250 & 11 & 0.091667 & 0.141667 & 0.000183 \tabularnewline
[2500,3000[ & 2750 & 11 & 0.091667 & 0.233333 & 0.000183 \tabularnewline
[3000,3500[ & 3250 & 12 & 0.1 & 0.333333 & 2e-04 \tabularnewline
[3500,4000[ & 3750 & 15 & 0.125 & 0.458333 & 0.00025 \tabularnewline
[4000,4500[ & 4250 & 50 & 0.416667 & 0.875 & 0.000833 \tabularnewline
[4500,5000] & 4750 & 15 & 0.125 & 1 & 0.00025 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306777&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][1000,1500[[/C][C]1250[/C][C]1[/C][C]0.008333[/C][C]0.008333[/C][C]1.7e-05[/C][/ROW]
[ROW][C][1500,2000[[/C][C]1750[/C][C]5[/C][C]0.041667[/C][C]0.05[/C][C]8.3e-05[/C][/ROW]
[ROW][C][2000,2500[[/C][C]2250[/C][C]11[/C][C]0.091667[/C][C]0.141667[/C][C]0.000183[/C][/ROW]
[ROW][C][2500,3000[[/C][C]2750[/C][C]11[/C][C]0.091667[/C][C]0.233333[/C][C]0.000183[/C][/ROW]
[ROW][C][3000,3500[[/C][C]3250[/C][C]12[/C][C]0.1[/C][C]0.333333[/C][C]2e-04[/C][/ROW]
[ROW][C][3500,4000[[/C][C]3750[/C][C]15[/C][C]0.125[/C][C]0.458333[/C][C]0.00025[/C][/ROW]
[ROW][C][4000,4500[[/C][C]4250[/C][C]50[/C][C]0.416667[/C][C]0.875[/C][C]0.000833[/C][/ROW]
[ROW][C][4500,5000][/C][C]4750[/C][C]15[/C][C]0.125[/C][C]1[/C][C]0.00025[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306777&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306777&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
[1000,1500[125010.0083330.0083331.7e-05
[1500,2000[175050.0416670.058.3e-05
[2000,2500[2250110.0916670.1416670.000183
[2500,3000[2750110.0916670.2333330.000183
[3000,3500[3250120.10.3333332e-04
[3500,4000[3750150.1250.4583330.00025
[4000,4500[4250500.4166670.8750.000833
[4500,5000]4750150.12510.00025


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):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- ''
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')
}