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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 computationWed, 10 Aug 2016 14:12:15 +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/Aug/10/t1470834764jdxxj3uqaoz34wl.htm/, Retrieved Tue, 30 Apr 2024 07:36:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296199, Retrieved Tue, 30 Apr 2024 07:36:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Reeks A Stap 2] [2016-08-10 12:55:02] [74be16979710d4c4e7c6647856088456]
- R PD  [Univariate Data Series] [Reeks A Stap 2] [2016-08-10 13:08:22] [74be16979710d4c4e7c6647856088456]
- RMP       [Histogram] [Reeks A Stap 3] [2016-08-10 13:12:15] [d41d8cd98f00b204e9800998ecf8427e] [Current]
- RMP         [Kernel Density Estimation] [Reeks A Stap 6] [2016-08-10 15:27:41] [74be16979710d4c4e7c6647856088456]
- RMPD          [Quartiles] [Reeks A Stap 8] [2016-08-10 16:02:58] [74be16979710d4c4e7c6647856088456]
- RMPD          [Notched Boxplots] [Reeks A Stap 9] [2016-08-10 16:13:19] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
567
557
547
527
729
719
567
466
476
476
486
507
446
385
335
335
527
547
395
223
314
314
385
426
416
314
365
345
517
476
314
193
304
335
365
405
324
254
284
294
557
557
405
385
446
416
497
598
618
476
436
395
669
689
638
689
679
598
689
790
831
709
628
689
952
1.033
1.013
1.053
1.043
942
1.114
1.155
1.215
1.033
962
1.043
1.236
1.408
1.367
1.367
1.387
1.317
1.499
1.499
1.468
1.296
1.327
1.347
1.479
1.651
1.529
1.590
1.539
1.509
1.742
1.691
1.620
1.519
1.620
1.671
1.732
1.813
1.732
1.782
1.721
1.711
1.964
1.985
1.904
1.762
1.883
1.934
1.995
2.086
1.995
2.066
2.035
1.924
2.157
2.157

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=296199&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=296199&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296199&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
[0,100[50530.4416670.4416670.004417
[100,200[15010.0083330.458.3e-05
[200,300[25040.0333330.4833330.000333
[300,400[350170.1416670.6250.001417
[400,500[450150.1250.750.00125
[500,600[550130.1083330.8583330.001083
[600,700[65090.0750.9333330.00075
[700,800[75040.0333330.9666670.000333
[800,900[85010.0083330.9758.3e-05
[900,1000]95030.02510.00025

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,100[ & 50 & 53 & 0.441667 & 0.441667 & 0.004417 \tabularnewline
[100,200[ & 150 & 1 & 0.008333 & 0.45 & 8.3e-05 \tabularnewline
[200,300[ & 250 & 4 & 0.033333 & 0.483333 & 0.000333 \tabularnewline
[300,400[ & 350 & 17 & 0.141667 & 0.625 & 0.001417 \tabularnewline
[400,500[ & 450 & 15 & 0.125 & 0.75 & 0.00125 \tabularnewline
[500,600[ & 550 & 13 & 0.108333 & 0.858333 & 0.001083 \tabularnewline
[600,700[ & 650 & 9 & 0.075 & 0.933333 & 0.00075 \tabularnewline
[700,800[ & 750 & 4 & 0.033333 & 0.966667 & 0.000333 \tabularnewline
[800,900[ & 850 & 1 & 0.008333 & 0.975 & 8.3e-05 \tabularnewline
[900,1000] & 950 & 3 & 0.025 & 1 & 0.00025 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296199&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][0,100[[/C][C]50[/C][C]53[/C][C]0.441667[/C][C]0.441667[/C][C]0.004417[/C][/ROW]
[ROW][C][100,200[[/C][C]150[/C][C]1[/C][C]0.008333[/C][C]0.45[/C][C]8.3e-05[/C][/ROW]
[ROW][C][200,300[[/C][C]250[/C][C]4[/C][C]0.033333[/C][C]0.483333[/C][C]0.000333[/C][/ROW]
[ROW][C][300,400[[/C][C]350[/C][C]17[/C][C]0.141667[/C][C]0.625[/C][C]0.001417[/C][/ROW]
[ROW][C][400,500[[/C][C]450[/C][C]15[/C][C]0.125[/C][C]0.75[/C][C]0.00125[/C][/ROW]
[ROW][C][500,600[[/C][C]550[/C][C]13[/C][C]0.108333[/C][C]0.858333[/C][C]0.001083[/C][/ROW]
[ROW][C][600,700[[/C][C]650[/C][C]9[/C][C]0.075[/C][C]0.933333[/C][C]0.00075[/C][/ROW]
[ROW][C][700,800[[/C][C]750[/C][C]4[/C][C]0.033333[/C][C]0.966667[/C][C]0.000333[/C][/ROW]
[ROW][C][800,900[[/C][C]850[/C][C]1[/C][C]0.008333[/C][C]0.975[/C][C]8.3e-05[/C][/ROW]
[ROW][C][900,1000][/C][C]950[/C][C]3[/C][C]0.025[/C][C]1[/C][C]0.00025[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296199&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296199&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
[0,100[50530.4416670.4416670.004417
[100,200[15010.0083330.458.3e-05
[200,300[25040.0333330.4833330.000333
[300,400[350170.1416670.6250.001417
[400,500[450150.1250.750.00125
[500,600[550130.1083330.8583330.001083
[600,700[65090.0750.9333330.00075
[700,800[75040.0333330.9666670.000333
[800,900[85010.0083330.9758.3e-05
[900,1000]95030.02510.00025


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):
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,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')
}