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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 computationFri, 23 Dec 2011 07:54:52 -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/23/t1324644929y6f1jy496fssimk.htm/, Retrieved Mon, 29 Apr 2024 18:16:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=160362, Retrieved Mon, 29 Apr 2024 18:16:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact106

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Recursive Partitioning (Regression Trees)] [] [2010-12-05 19:50:12] [b98453cac15ba1066b407e146608df68]
- R PD  [Recursive Partitioning (Regression Trees)] [] [2011-12-09 10:41:59] [22f8bc702946f784836540059d0d9516]
- RMPD      [Histogram] [paper stat: beoor...] [2011-12-23 12:54:52] [9431a512beb885c6943db1a049152d0e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
140824
110459
105079
112098
43929
76173
187326
22807
144408
66485
79089
81625
68788
103297
69446
114948
167949
125081
125818
136588
112431
103037
82317
118906
83515
104581
103129
83243
37110
113344
139165
86652
112302
69652
119442
69867
101629
70168
31081
103925
92622
79011
93487
64520
93473
114360
33032
96125
151911
89256
95676
5950
149695
32551
31701
100087
169707
150491
120192
95893
151715
176225
59900
104767
114799
72128
143592
89626
131072
126817
81351
22618
88977
92059
81897
108146
126372
249771
71154
71571
55918
160141
38692
102812
56622
15986
123534
108535
93879
144551
56750
127654
65594
59938
146975
165904
169265
183500
165986
184923
140358
149959
57224
43750
48029
104978
100046
101047
197426
160902
147172
109432
1168
83248
25162
45724
110529
855
101382
14116
89506
135356
116066
144244
8773
102153
117440
104128
134238
134047
279488
79756
66089
102070
146760
154771
165933
64593
92280
67150
128692
124089
125386
37238
140015
150047
154451
156349

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'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160362&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160362&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160362&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'AstonUniversity' @ aston.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,50000[25000200.1351350.1351353e-06
[50000,1e+05[75000450.3040540.4391896e-06
[1e+05,150000[125000610.4121620.8513518e-06
[150000,2e+05[175000200.1351350.9864863e-06
[2e+05,250000[22500010.0067570.9932430
[250000,3e+05]27500010.00675710

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,50000[ & 25000 & 20 & 0.135135 & 0.135135 & 3e-06 \tabularnewline
[50000,1e+05[ & 75000 & 45 & 0.304054 & 0.439189 & 6e-06 \tabularnewline
[1e+05,150000[ & 125000 & 61 & 0.412162 & 0.851351 & 8e-06 \tabularnewline
[150000,2e+05[ & 175000 & 20 & 0.135135 & 0.986486 & 3e-06 \tabularnewline
[2e+05,250000[ & 225000 & 1 & 0.006757 & 0.993243 & 0 \tabularnewline
[250000,3e+05] & 275000 & 1 & 0.006757 & 1 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160362&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][0,50000[[/C][C]25000[/C][C]20[/C][C]0.135135[/C][C]0.135135[/C][C]3e-06[/C][/ROW]
[ROW][C][50000,1e+05[[/C][C]75000[/C][C]45[/C][C]0.304054[/C][C]0.439189[/C][C]6e-06[/C][/ROW]
[ROW][C][1e+05,150000[[/C][C]125000[/C][C]61[/C][C]0.412162[/C][C]0.851351[/C][C]8e-06[/C][/ROW]
[ROW][C][150000,2e+05[[/C][C]175000[/C][C]20[/C][C]0.135135[/C][C]0.986486[/C][C]3e-06[/C][/ROW]
[ROW][C][2e+05,250000[[/C][C]225000[/C][C]1[/C][C]0.006757[/C][C]0.993243[/C][C]0[/C][/ROW]
[ROW][C][250000,3e+05][/C][C]275000[/C][C]1[/C][C]0.006757[/C][C]1[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160362&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160362&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
[0,50000[25000200.1351350.1351353e-06
[50000,1e+05[75000450.3040540.4391896e-06
[1e+05,150000[125000610.4121620.8513518e-06
[150000,2e+05[175000200.1351350.9864863e-06
[2e+05,250000[22500010.0067570.9932430
[250000,3e+05]27500010.00675710


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = none ; par3 = 3 ; par4 = no ;
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')
}