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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, 16 Dec 2011 16:57:04 -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/16/t1324072641bh0dhnhkl3741sc.htm/, Retrieved Sun, 05 May 2024 14:13:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=156138, Retrieved Sun, 05 May 2024 14:13:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [(Partial) Autocorrelation Function] [Births] [2010-11-29 09:36:27] [b98453cac15ba1066b407e146608df68]
- R P           [(Partial) Autocorrelation Function] [Maandelijkse gebo...] [2011-12-04 13:29:13] [74be16979710d4c4e7c6647856088456]
- RMPD              [Histogram] [] [2011-12-16 21:57:04] [dfe1aa60d86cf4207f33712af6589424] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
112285
84786
83123
101193
38361
68504
119182
22807
17140
116174
57635
66198
71701
57793
80444
53855
97668
133824
101481
99645
114789
99052
67654
65553
97500
69112
82753
85323
72654
30727
77873
117478
74007
90183
61542
101494
27570
55813
79215
1423
55461
31081
22996
83122
70106
60578
39992
79892
49810
71570
100708
33032
82875
139077
71595
72260
5950
115762
32551
31701
80670
143558
117105
23789
120733
105195
73107
132068
149193
46821
87011
95260
55183
106671
73511
92945
78664
70054
22618
74011
83737
69094
93133
95536
225920
62133
61370
43836
106117
38692
84651
56622
15986
95364
26706
89691
67267
126846
41140
102860
51715
55801
111813
120293
138599
161647
115929
24266
162901
109825
129838
37510
43750
40652
87771
85872
89275
44418
192565
35232
40909
13294
32387
140867
120662
21233
44332
61056
101338
1168
13497
65567
25162
32334
40735
91413
855
97068
44339
14116
10288
65622
16563
76643
110681
29011
92696
94785
8773
83209
93815
86687
34553
105547
103487
213688
71220
23517
56926
91721
115168
111194
51009
135777
51513
74163
51633
75345
33416
83305
98952
102372
37238
103772
123969
27142
135400
21399
130115
24874
34988
45549
6023
64466
54990
1644
6179
3926
32755
34777
73224
27114
20760
37636
65461
30080
24094
69008
54968
46090
27507
10672
34029
46300
24760
18779
21280
40662
28987
22827
18513
30594
24006
27913
42744
12934
22574
41385
18653
18472
30976
63339
25568
33747
4154
19474
35130
39067
13310
65892
4143
28579
51776
21152
38084
27717
32928
11342
19499
16380
36874
48259
16734
28207
30143
41369
45833
29156
35944
36278
45588
45097
3895
28394
18632
2325
25139
27975
14483
13127
5839
24069
3738
18625
36341
24548
21792
26263
23686
49303
25659
28904
2781
29236
19546
22818
32689
5752
22197
20055
25272
82206
32073
5444
20154
36944
8019
30884
19540

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'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156138&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156138&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156138&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'George Udny Yule' @ yule.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,20000[10000440.1522490.1522498e-06
[20000,40000[30000840.2906570.4429071.5e-05
[40000,60000[50000390.1349480.5778557e-06
[60000,80000[70000390.1349480.7128037e-06
[80000,1e+05[90000360.1245670.837376e-06
[1e+05,120000[110000260.0899650.9273364e-06
[120000,140000[130000130.0449830.9723182e-06
[140000,160000[15000030.0103810.9826991e-06
[160000,180000[17000020.006920.9896190
[180000,2e+05[19000010.003460.993080
[2e+05,220000[21000010.003460.996540
[220000,240000]23000010.0034610

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,20000[ & 10000 & 44 & 0.152249 & 0.152249 & 8e-06 \tabularnewline
[20000,40000[ & 30000 & 84 & 0.290657 & 0.442907 & 1.5e-05 \tabularnewline
[40000,60000[ & 50000 & 39 & 0.134948 & 0.577855 & 7e-06 \tabularnewline
[60000,80000[ & 70000 & 39 & 0.134948 & 0.712803 & 7e-06 \tabularnewline
[80000,1e+05[ & 90000 & 36 & 0.124567 & 0.83737 & 6e-06 \tabularnewline
[1e+05,120000[ & 110000 & 26 & 0.089965 & 0.927336 & 4e-06 \tabularnewline
[120000,140000[ & 130000 & 13 & 0.044983 & 0.972318 & 2e-06 \tabularnewline
[140000,160000[ & 150000 & 3 & 0.010381 & 0.982699 & 1e-06 \tabularnewline
[160000,180000[ & 170000 & 2 & 0.00692 & 0.989619 & 0 \tabularnewline
[180000,2e+05[ & 190000 & 1 & 0.00346 & 0.99308 & 0 \tabularnewline
[2e+05,220000[ & 210000 & 1 & 0.00346 & 0.99654 & 0 \tabularnewline
[220000,240000] & 230000 & 1 & 0.00346 & 1 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156138&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][0,20000[[/C][C]10000[/C][C]44[/C][C]0.152249[/C][C]0.152249[/C][C]8e-06[/C][/ROW]
[ROW][C][20000,40000[[/C][C]30000[/C][C]84[/C][C]0.290657[/C][C]0.442907[/C][C]1.5e-05[/C][/ROW]
[ROW][C][40000,60000[[/C][C]50000[/C][C]39[/C][C]0.134948[/C][C]0.577855[/C][C]7e-06[/C][/ROW]
[ROW][C][60000,80000[[/C][C]70000[/C][C]39[/C][C]0.134948[/C][C]0.712803[/C][C]7e-06[/C][/ROW]
[ROW][C][80000,1e+05[[/C][C]90000[/C][C]36[/C][C]0.124567[/C][C]0.83737[/C][C]6e-06[/C][/ROW]
[ROW][C][1e+05,120000[[/C][C]110000[/C][C]26[/C][C]0.089965[/C][C]0.927336[/C][C]4e-06[/C][/ROW]
[ROW][C][120000,140000[[/C][C]130000[/C][C]13[/C][C]0.044983[/C][C]0.972318[/C][C]2e-06[/C][/ROW]
[ROW][C][140000,160000[[/C][C]150000[/C][C]3[/C][C]0.010381[/C][C]0.982699[/C][C]1e-06[/C][/ROW]
[ROW][C][160000,180000[[/C][C]170000[/C][C]2[/C][C]0.00692[/C][C]0.989619[/C][C]0[/C][/ROW]
[ROW][C][180000,2e+05[[/C][C]190000[/C][C]1[/C][C]0.00346[/C][C]0.99308[/C][C]0[/C][/ROW]
[ROW][C][2e+05,220000[[/C][C]210000[/C][C]1[/C][C]0.00346[/C][C]0.99654[/C][C]0[/C][/ROW]
[ROW][C][220000,240000][/C][C]230000[/C][C]1[/C][C]0.00346[/C][C]1[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156138&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156138&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
[0,20000[10000440.1522490.1522498e-06
[20000,40000[30000840.2906570.4429071.5e-05
[40000,60000[50000390.1349480.5778557e-06
[60000,80000[70000390.1349480.7128037e-06
[80000,1e+05[90000360.1245670.837376e-06
[1e+05,120000[110000260.0899650.9273364e-06
[120000,140000[130000130.0449830.9723182e-06
[140000,160000[15000030.0103810.9826991e-06
[160000,180000[17000020.006920.9896190
[180000,2e+05[19000010.003460.993080
[2e+05,220000[21000010.003460.996540
[220000,240000]23000010.0034610


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')
}