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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, 21 Dec 2011 13:33:32 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/21/t1324492594e1verhhspv11ol0.htm/, Retrieved Wed, 08 May 2024 00:59:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=158937, Retrieved Wed, 08 May 2024 00:59:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact76

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [paper-frequency p...] [2011-12-21 18:33:32] [fe2dc4bc83c881ccd49ef12feaba2b65] [Current]
- RMP     [Stem-and-leaf Plot] [paper-stem and le...] [2011-12-22 10:02:22] [c2267e575f67090c7e8d960bdccd246a]
- RMP       [Central Tendency] [paper-central ten...] [2011-12-22 10:23:41] [c2267e575f67090c7e8d960bdccd246a]
- R  D        [Central Tendency] [paper-central ten...] [2011-12-23 16:00:30] [c2267e575f67090c7e8d960bdccd246a]
- R  D    [Histogram] [paper-frequency p...] [2011-12-23 15:55:57] [c2267e575f67090c7e8d960bdccd246a]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
539
548
563
581
572
519
521
531
540
548
556
551
549
564
586
604
601
545
537
552
563
575
580
575
558
564
581
597
587
536
524
537
536
533
528
516
502
506
518
534
528
478
469
490
493
508
517
514
510
527
542
565
555
499
511
526
532
549
561
557
566
588
620
626
620
573
573
574
580
590

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158937&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]0 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=158937&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158937&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 time0 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[460,480[47020.0285710.0285710.001429
[480,500[49030.0428570.0714290.002143
[500,520[510100.1428570.2142860.007143
[520,540[530150.2142860.4285710.010714
[540,560[550130.1857140.6142860.009286
[560,580[570130.1857140.80.009286
[580,600[59090.1285710.9285710.006429
[600,620[61020.0285710.9571430.001429
[620,640]63030.04285710.002143

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[460,480[ & 470 & 2 & 0.028571 & 0.028571 & 0.001429 \tabularnewline
[480,500[ & 490 & 3 & 0.042857 & 0.071429 & 0.002143 \tabularnewline
[500,520[ & 510 & 10 & 0.142857 & 0.214286 & 0.007143 \tabularnewline
[520,540[ & 530 & 15 & 0.214286 & 0.428571 & 0.010714 \tabularnewline
[540,560[ & 550 & 13 & 0.185714 & 0.614286 & 0.009286 \tabularnewline
[560,580[ & 570 & 13 & 0.185714 & 0.8 & 0.009286 \tabularnewline
[580,600[ & 590 & 9 & 0.128571 & 0.928571 & 0.006429 \tabularnewline
[600,620[ & 610 & 2 & 0.028571 & 0.957143 & 0.001429 \tabularnewline
[620,640] & 630 & 3 & 0.042857 & 1 & 0.002143 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158937&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][460,480[[/C][C]470[/C][C]2[/C][C]0.028571[/C][C]0.028571[/C][C]0.001429[/C][/ROW]
[ROW][C][480,500[[/C][C]490[/C][C]3[/C][C]0.042857[/C][C]0.071429[/C][C]0.002143[/C][/ROW]
[ROW][C][500,520[[/C][C]510[/C][C]10[/C][C]0.142857[/C][C]0.214286[/C][C]0.007143[/C][/ROW]
[ROW][C][520,540[[/C][C]530[/C][C]15[/C][C]0.214286[/C][C]0.428571[/C][C]0.010714[/C][/ROW]
[ROW][C][540,560[[/C][C]550[/C][C]13[/C][C]0.185714[/C][C]0.614286[/C][C]0.009286[/C][/ROW]
[ROW][C][560,580[[/C][C]570[/C][C]13[/C][C]0.185714[/C][C]0.8[/C][C]0.009286[/C][/ROW]
[ROW][C][580,600[[/C][C]590[/C][C]9[/C][C]0.128571[/C][C]0.928571[/C][C]0.006429[/C][/ROW]
[ROW][C][600,620[[/C][C]610[/C][C]2[/C][C]0.028571[/C][C]0.957143[/C][C]0.001429[/C][/ROW]
[ROW][C][620,640][/C][C]630[/C][C]3[/C][C]0.042857[/C][C]1[/C][C]0.002143[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158937&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158937&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
[460,480[47020.0285710.0285710.001429
[480,500[49030.0428570.0714290.002143
[500,520[510100.1428570.2142860.007143
[520,540[530150.2142860.4285710.010714
[540,560[550130.1857140.6142860.009286
[560,580[570130.1857140.80.009286
[580,600[59090.1285710.9285710.006429
[600,620[61020.0285710.9571430.001429
[620,640]63030.04285710.002143


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')
}