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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 computationSun, 15 Jan 2012 10:26:20 -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/2012/Jan/15/t1326641335ucp3cl0ag0i2pwk.htm/, Retrieved Fri, 03 May 2024 06:09:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=161085, Retrieved Fri, 03 May 2024 06:09:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDG2011W2EC
Estimated Impact161

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] [personenwagens] [2011-09-28 18:40:56] [7b3043afb616d282b5e47ed3b5b59e09]
- RMP     [Histogram] [opgave 2 oef 2] [2012-01-15 15:26:20] [9bda411d6223d16f0472c7feaae49b5f] [Current]
- RMP       [Kernel Density Estimation] [opgave 2 oef 2] [2012-01-15 15:34:31] [0f3802131247472a006387bf3e5d274d]
- RMPD      [Notched Boxplots] [opgave 3 oef 1] [2012-01-15 15:49:05] [0f3802131247472a006387bf3e5d274d]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
45504
40129
40357
41913
33730
37842
33025
24050
30429
34507
25189
20253
48527
44446
46380
48950
38883
42928
37107
30186
32602
39892
32194
21629
59968
45694
55756
48554
41052
49822
39191
31994
35735
38930
33658
23849
58972
59249
63955
53785
52760
44795
37348
32370
32717
40974
33591
21124
58608
46865
51378
46235
47206
45382
41227
33795
31295
42625
33625
21538
56421
53152
53536
52408
41454
38271
35306
26414
31917
38030
27534
18387

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=161085&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=161085&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161085&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
[15000,20000[1750010.0138890.0138893e-06
[20000,25000[2250060.0833330.0972221.7e-05
[25000,30000[2750030.0416670.1388898e-06
[30000,35000[32500160.2222220.3611114.4e-05
[35000,40000[37500110.1527780.5138893.1e-05
[40000,45000[42500110.1527780.6666673.1e-05
[45000,50000[47500110.1527780.8194443.1e-05
[50000,55000[5250060.0833330.9027781.7e-05
[55000,60000[5750060.0833330.9861111.7e-05
[60000,65000]6250010.01388913e-06

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[15000,20000[ & 17500 & 1 & 0.013889 & 0.013889 & 3e-06 \tabularnewline
[20000,25000[ & 22500 & 6 & 0.083333 & 0.097222 & 1.7e-05 \tabularnewline
[25000,30000[ & 27500 & 3 & 0.041667 & 0.138889 & 8e-06 \tabularnewline
[30000,35000[ & 32500 & 16 & 0.222222 & 0.361111 & 4.4e-05 \tabularnewline
[35000,40000[ & 37500 & 11 & 0.152778 & 0.513889 & 3.1e-05 \tabularnewline
[40000,45000[ & 42500 & 11 & 0.152778 & 0.666667 & 3.1e-05 \tabularnewline
[45000,50000[ & 47500 & 11 & 0.152778 & 0.819444 & 3.1e-05 \tabularnewline
[50000,55000[ & 52500 & 6 & 0.083333 & 0.902778 & 1.7e-05 \tabularnewline
[55000,60000[ & 57500 & 6 & 0.083333 & 0.986111 & 1.7e-05 \tabularnewline
[60000,65000] & 62500 & 1 & 0.013889 & 1 & 3e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=161085&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][15000,20000[[/C][C]17500[/C][C]1[/C][C]0.013889[/C][C]0.013889[/C][C]3e-06[/C][/ROW]
[ROW][C][20000,25000[[/C][C]22500[/C][C]6[/C][C]0.083333[/C][C]0.097222[/C][C]1.7e-05[/C][/ROW]
[ROW][C][25000,30000[[/C][C]27500[/C][C]3[/C][C]0.041667[/C][C]0.138889[/C][C]8e-06[/C][/ROW]
[ROW][C][30000,35000[[/C][C]32500[/C][C]16[/C][C]0.222222[/C][C]0.361111[/C][C]4.4e-05[/C][/ROW]
[ROW][C][35000,40000[[/C][C]37500[/C][C]11[/C][C]0.152778[/C][C]0.513889[/C][C]3.1e-05[/C][/ROW]
[ROW][C][40000,45000[[/C][C]42500[/C][C]11[/C][C]0.152778[/C][C]0.666667[/C][C]3.1e-05[/C][/ROW]
[ROW][C][45000,50000[[/C][C]47500[/C][C]11[/C][C]0.152778[/C][C]0.819444[/C][C]3.1e-05[/C][/ROW]
[ROW][C][50000,55000[[/C][C]52500[/C][C]6[/C][C]0.083333[/C][C]0.902778[/C][C]1.7e-05[/C][/ROW]
[ROW][C][55000,60000[[/C][C]57500[/C][C]6[/C][C]0.083333[/C][C]0.986111[/C][C]1.7e-05[/C][/ROW]
[ROW][C][60000,65000][/C][C]62500[/C][C]1[/C][C]0.013889[/C][C]1[/C][C]3e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=161085&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161085&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
[15000,20000[1750010.0138890.0138893e-06
[20000,25000[2250060.0833330.0972221.7e-05
[25000,30000[2750030.0416670.1388898e-06
[30000,35000[32500160.2222220.3611114.4e-05
[35000,40000[37500110.1527780.5138893.1e-05
[40000,45000[42500110.1527780.6666673.1e-05
[45000,50000[47500110.1527780.8194443.1e-05
[50000,55000[5250060.0833330.9027781.7e-05
[55000,60000[5750060.0833330.9861111.7e-05
[60000,65000]6250010.01388913e-06


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')
}