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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 computationWed, 12 Dec 2012 10:33:07 -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/Dec/12/t1355326415mpdk8jdcskinohv.htm/, Retrieved Mon, 29 Apr 2024 04:17:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198936, Retrieved Mon, 29 Apr 2024 04:17:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Testing Mean with unknown Variance - Critical Value] [] [2010-10-25 13:12:27] [b98453cac15ba1066b407e146608df68]
- RMPD    [Histogram] [Histogram_Groep2:...] [2012-12-12 15:33:07] [5f6cd87c5735ffe37dbfae854ce1e663] [Current]
- RMPD      [Univariate Explorative Data Analysis] [Univariate EDA _G...] [2012-12-12 15:42:05] [f4325a5733446a4ce20d70c276c6a563]
- RMP       [Univariate Explorative Data Analysis] [Univariate EDA _G...] [2012-12-12 15:45:33] [f4325a5733446a4ce20d70c276c6a563]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
71,2850137
51,54016794
46,14902441
67,20296273
70,25647751
79,00062105
49,02089035
61,75876724
66,04816594
77,10834911
50,66480202
62,03758421
42,99810275
60,90026677
63,90814764
89,60429472
48,16319137
102,2152118
72,29179022
78,68118377
74,67784957
54,89432755
56,27814648
75,20973344
99,61523933
69,50133542
89,71261554
76,22043217
60,33511244
76,59757688
90,83361323
93,59054179
68,44063723
96,65537977
63,0184913
45,37877334
78,07757488
92,60685505
26,17181412
42,27109816
59,48912889
57,68145701
71,86890929
60,85057425
97,62822078
67,7813161
66,14905164
77,19835498
96,96717729
65,55050749
85,41174015
61,81741259
91,21355465
58,00810772
51,80162493
77,29376666
86,04604449
30,66235326
47,4785465
67,2134674
44,63874024
73,0812771
84,32222234
89,59617748
71,88971399
70,7203198
86,11128937
77,94128709
61,46492655
74,12674694
77,4673153
98,36136446
104,4100044
71,57435238
35,34634192
87,06073363
43,63452167
51,72229425
56,27289415
73,9447059
69,75157152
77,76625484
89,20423074
44,30668373
61,18825826
63,35310576
54,49262648
71,78335426
92,01047664
50,45484517
48,63249064
91,76095677
81,45305077
57,53942236
97,27310857
53,64761495
34,59246177
67,30681566
98,95931175
78,66624532
69,31989123
61,78010057
80,99156179
69,82844656
78,80628477
77,45693001
79,22002528
73,95659185
109,7070835
62,25473744
87,41379947
63,83205704
87,42508857
71,08358336
55,13999344
88,15294581
57,10480895
60,0609339
62,36466124
67,5432047
82,01402711
58,20452447
84,14047119
79,73560645
97,10107765
60,25446868
66,38458803
75,7358875
47,55617187
59,68912678
59,87868821
73,58234615
47,09205672
92,58543645
75,20606704
75,85212092
72,00775503
72,19895355
59,43183073
52,70939159
51,70783329
67,77551807
68,56173076
58,86232788
64,7414949
65,60683364
64,51269446
88,86542123
78,01267106
53,75528776
64,98364787
58,5592274
47,45017026
78,86088856
69,53003567
74,14224814
75,67052325
87,26608616
35,41209839
50,75920757
103,6577614
67,42451564
72,07840571
101,0205451
63,28213107
88,4256578
69,10961037
53,86623474
74,98845338
95,9200533
64,30359026
59,81375029
56,92285317
64,56419459
77,32089802
60,32240794
58,86232788
77,01605813
69,83992325
62,07586825
64,91806193
71,68170118
90,59248345
67,75346851
67,1328748
87,81860419
70,40797659
66,97728299
66,08261305
73,41490249
67,22980419
83,12080258
47,18373379
64,37874294
43,10185336
77,18418391
50,99457343
91,39288426
60,07094402
63,02616516

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198936&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198936&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198936&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 time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[20,30[2510.0050.0055e-04
[30,40[3540.020.0250.002
[40,50[45160.080.1050.008
[50,60[55310.1550.260.0155
[60,70[65550.2750.5350.0275
[70,80[75490.2450.780.0245
[80,90[85210.1050.8850.0105
[90,100[95180.090.9750.009
[100,110]10550.02510.0025

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[20,30[ & 25 & 1 & 0.005 & 0.005 & 5e-04 \tabularnewline
[30,40[ & 35 & 4 & 0.02 & 0.025 & 0.002 \tabularnewline
[40,50[ & 45 & 16 & 0.08 & 0.105 & 0.008 \tabularnewline
[50,60[ & 55 & 31 & 0.155 & 0.26 & 0.0155 \tabularnewline
[60,70[ & 65 & 55 & 0.275 & 0.535 & 0.0275 \tabularnewline
[70,80[ & 75 & 49 & 0.245 & 0.78 & 0.0245 \tabularnewline
[80,90[ & 85 & 21 & 0.105 & 0.885 & 0.0105 \tabularnewline
[90,100[ & 95 & 18 & 0.09 & 0.975 & 0.009 \tabularnewline
[100,110] & 105 & 5 & 0.025 & 1 & 0.0025 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198936&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][20,30[[/C][C]25[/C][C]1[/C][C]0.005[/C][C]0.005[/C][C]5e-04[/C][/ROW]
[ROW][C][30,40[[/C][C]35[/C][C]4[/C][C]0.02[/C][C]0.025[/C][C]0.002[/C][/ROW]
[ROW][C][40,50[[/C][C]45[/C][C]16[/C][C]0.08[/C][C]0.105[/C][C]0.008[/C][/ROW]
[ROW][C][50,60[[/C][C]55[/C][C]31[/C][C]0.155[/C][C]0.26[/C][C]0.0155[/C][/ROW]
[ROW][C][60,70[[/C][C]65[/C][C]55[/C][C]0.275[/C][C]0.535[/C][C]0.0275[/C][/ROW]
[ROW][C][70,80[[/C][C]75[/C][C]49[/C][C]0.245[/C][C]0.78[/C][C]0.0245[/C][/ROW]
[ROW][C][80,90[[/C][C]85[/C][C]21[/C][C]0.105[/C][C]0.885[/C][C]0.0105[/C][/ROW]
[ROW][C][90,100[[/C][C]95[/C][C]18[/C][C]0.09[/C][C]0.975[/C][C]0.009[/C][/ROW]
[ROW][C][100,110][/C][C]105[/C][C]5[/C][C]0.025[/C][C]1[/C][C]0.0025[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198936&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198936&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
[20,30[2510.0050.0055e-04
[30,40[3540.020.0250.002
[40,50[45160.080.1050.008
[50,60[55310.1550.260.0155
[60,70[65550.2750.5350.0275
[70,80[75490.2450.780.0245
[80,90[85210.1050.8850.0105
[90,100[95180.090.9750.009
[100,110]10550.02510.0025


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')
}