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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 computationTue, 27 Sep 2011 20:17:52 -0400
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/Sep/27/t1317169127ltsql225dv3x0hj.htm/, Retrieved Fri, 03 May 2024 21:01:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=124501, Retrieved Fri, 03 May 2024 21:01:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W1
Estimated Impact111

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [frequentietabel] [2011-09-28 00:17:52] [480fcaba71e70207c3e0ad7177944aa6] [Current]
- RM      [Histogram] [frequentietabel v...] [2011-10-04 17:32:24] [226376a35b8869827dc57271384c00a4]
- RMP     [Kernel Density Estimation] [dichtheidsgrafiek...] [2011-10-04 17:41:39] [226376a35b8869827dc57271384c00a4]
- RMP     [Kernel Density Estimation] [dichtheidsgrafiek...] [2011-10-04 17:45:23] [226376a35b8869827dc57271384c00a4]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2144
2207
1864
2061
2025
2068
2054
2095
2151
2065
2147
1994
2273
2119
1969
1821
1942
1802
1737
1650
1720
1491
1570
1649
1409
1480
1495
1490
1415
1448
1354
1330
1183
1264
1197
1037
1084
1103
1005
1013
973
1046
923
844
820
777
652
560
490
582
505
478
540
585
594
586
585
534
588
581
615
603
626
687
580
539
550
606
597
539
551
526
636
518
593
549
553
615
601
571

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=124501&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=124501&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124501&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
[400,600[500250.31250.31250.001562
[600,800[700100.1250.43750.000625
[800,1000[90040.050.48750.00025
[1000,1200[110080.10.58755e-04
[1200,1400[130030.03750.6250.000188
[1400,1600[150080.10.7255e-04
[1600,1800[170040.050.7750.00025
[1800,2000[190060.0750.850.000375
[2000,2200[2100100.1250.9750.000625
[2200,2400]230020.02510.000125

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[400,600[ & 500 & 25 & 0.3125 & 0.3125 & 0.001562 \tabularnewline
[600,800[ & 700 & 10 & 0.125 & 0.4375 & 0.000625 \tabularnewline
[800,1000[ & 900 & 4 & 0.05 & 0.4875 & 0.00025 \tabularnewline
[1000,1200[ & 1100 & 8 & 0.1 & 0.5875 & 5e-04 \tabularnewline
[1200,1400[ & 1300 & 3 & 0.0375 & 0.625 & 0.000188 \tabularnewline
[1400,1600[ & 1500 & 8 & 0.1 & 0.725 & 5e-04 \tabularnewline
[1600,1800[ & 1700 & 4 & 0.05 & 0.775 & 0.00025 \tabularnewline
[1800,2000[ & 1900 & 6 & 0.075 & 0.85 & 0.000375 \tabularnewline
[2000,2200[ & 2100 & 10 & 0.125 & 0.975 & 0.000625 \tabularnewline
[2200,2400] & 2300 & 2 & 0.025 & 1 & 0.000125 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124501&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][400,600[[/C][C]500[/C][C]25[/C][C]0.3125[/C][C]0.3125[/C][C]0.001562[/C][/ROW]
[ROW][C][600,800[[/C][C]700[/C][C]10[/C][C]0.125[/C][C]0.4375[/C][C]0.000625[/C][/ROW]
[ROW][C][800,1000[[/C][C]900[/C][C]4[/C][C]0.05[/C][C]0.4875[/C][C]0.00025[/C][/ROW]
[ROW][C][1000,1200[[/C][C]1100[/C][C]8[/C][C]0.1[/C][C]0.5875[/C][C]5e-04[/C][/ROW]
[ROW][C][1200,1400[[/C][C]1300[/C][C]3[/C][C]0.0375[/C][C]0.625[/C][C]0.000188[/C][/ROW]
[ROW][C][1400,1600[[/C][C]1500[/C][C]8[/C][C]0.1[/C][C]0.725[/C][C]5e-04[/C][/ROW]
[ROW][C][1600,1800[[/C][C]1700[/C][C]4[/C][C]0.05[/C][C]0.775[/C][C]0.00025[/C][/ROW]
[ROW][C][1800,2000[[/C][C]1900[/C][C]6[/C][C]0.075[/C][C]0.85[/C][C]0.000375[/C][/ROW]
[ROW][C][2000,2200[[/C][C]2100[/C][C]10[/C][C]0.125[/C][C]0.975[/C][C]0.000625[/C][/ROW]
[ROW][C][2200,2400][/C][C]2300[/C][C]2[/C][C]0.025[/C][C]1[/C][C]0.000125[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124501&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124501&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
[400,600[500250.31250.31250.001562
[600,800[700100.1250.43750.000625
[800,1000[90040.050.48750.00025
[1000,1200[110080.10.58755e-04
[1200,1400[130030.03750.6250.000188
[1400,1600[150080.10.7255e-04
[1600,1800[170040.050.7750.00025
[1800,2000[190060.0750.850.000375
[2000,2200[2100100.1250.9750.000625
[2200,2400]230020.02510.000125


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')
}