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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 computationThu, 22 Dec 2011 06:29:25 -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/22/t1324553381qf3ut0hcc703qap.htm/, Retrieved Mon, 29 Apr 2024 20:07:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=159330, Retrieved Mon, 29 Apr 2024 20:07:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Paper - Deel 1 - ...] [2011-12-22 11:29:25] [a30255a61f2fa55603799e7bfe8f38bd] [Current]
- R P     [Histogram] [Paper - Deel 1 - ...] [2011-12-22 11:40:54] [95a4a8598e82ac3272c4dca488d0ba38]
- RMP     [Percentiles] [Paper - Deel 1 - ...] [2011-12-22 11:47:58] [95a4a8598e82ac3272c4dca488d0ba38]
- R  D      [Percentiles] [Paper 1.3 Q-Q plot] [2012-12-17 16:06:48] [d5c5f9d2d41487720068c665b8e94d36]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
186099
113854
99776
106194
100792
47552
250931
6853
115466
110896
169351
94853
72591
101345
113713
165354
164263
135213
111669
134163
140303
150773
111848
102509
96785
116136
158376
153990
64057
230054
184531
114198
198299
33750
189723
100826
188355
104470
58391
164808
134097
80238
133252
54518
121850
79367
56968
106314
191889
104864
160792
15049
191179
25109
45824
129711
210012
194679
197680
81180
197765
214738
96252
124527
153242
145707
113963
134904
114268
94333
102204
23824
111563
91313
89770
100125
165278
181712
80906
75881
83963
175721
68580
136323
55792
25157
100922
118845
170492
81716
115750
105590
92795
82390
135599
127667
163073
211381
189944
226168
117495
195894
80684
19630
88634
139292
128602
135848
178377
106330
178303
116938
5841
106020
24610
74151
232241
6622
127097
13155
160501
91502
24469
88229
13983
80716
157384
122975
191469
231257
258287
122531
61394
86480
195791
18284
147581
72558
147341
114651
100187
130332
134218
10901
145758
75767
134969
169216
0
7953
0
0
0
0
105406
174586
0
0
4245
21509
7670
15673
0
75882

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159330&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159330&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159330&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'Gwilym Jenkins' @ jenkins.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,50000[25000300.1829270.1829274e-06
[50000,1e+05[75000340.2073170.3902444e-06
[1e+05,150000[125000570.3475610.7378057e-06
[150000,2e+05[175000340.2073170.9451224e-06
[2e+05,250000[22500070.0426830.9878051e-06
[250000,3e+05]27500020.01219510

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,50000[ & 25000 & 30 & 0.182927 & 0.182927 & 4e-06 \tabularnewline
[50000,1e+05[ & 75000 & 34 & 0.207317 & 0.390244 & 4e-06 \tabularnewline
[1e+05,150000[ & 125000 & 57 & 0.347561 & 0.737805 & 7e-06 \tabularnewline
[150000,2e+05[ & 175000 & 34 & 0.207317 & 0.945122 & 4e-06 \tabularnewline
[2e+05,250000[ & 225000 & 7 & 0.042683 & 0.987805 & 1e-06 \tabularnewline
[250000,3e+05] & 275000 & 2 & 0.012195 & 1 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159330&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]30[/C][C]0.182927[/C][C]0.182927[/C][C]4e-06[/C][/ROW]
[ROW][C][50000,1e+05[[/C][C]75000[/C][C]34[/C][C]0.207317[/C][C]0.390244[/C][C]4e-06[/C][/ROW]
[ROW][C][1e+05,150000[[/C][C]125000[/C][C]57[/C][C]0.347561[/C][C]0.737805[/C][C]7e-06[/C][/ROW]
[ROW][C][150000,2e+05[[/C][C]175000[/C][C]34[/C][C]0.207317[/C][C]0.945122[/C][C]4e-06[/C][/ROW]
[ROW][C][2e+05,250000[[/C][C]225000[/C][C]7[/C][C]0.042683[/C][C]0.987805[/C][C]1e-06[/C][/ROW]
[ROW][C][250000,3e+05][/C][C]275000[/C][C]2[/C][C]0.012195[/C][C]1[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159330&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159330&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[25000300.1829270.1829274e-06
[50000,1e+05[75000340.2073170.3902444e-06
[1e+05,150000[125000570.3475610.7378057e-06
[150000,2e+05[175000340.2073170.9451224e-06
[2e+05,250000[22500070.0426830.9878051e-06
[250000,3e+05]27500020.01219510


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')
}