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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, 10 Dec 2014 13:00:22 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/10/t1418216459f7v6nfpgfm28rgc.htm/, Retrieved Sun, 19 May 2024 16:38:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265078, Retrieved Sun, 19 May 2024 16:38:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [1.1 AMSI - histogram] [2014-12-09 11:36:56] [4d39cf209776852399955073f9d0ee7a]
- R  D    [Histogram] [1.1 AMSE : Histog...] [2014-12-10 13:00:22] [706bcb1d0c5210dc074174906fafd7a3] [Current]
-    D      [Histogram] [1.1 AMSE : Histog...] [2014-12-10 13:05:51] [765bd0d5d4a0c852014c120c6930661d]
- RMPD      [Cronbach Alpha] [1.1 AMSI : Cronba...] [2014-12-10 13:58:26] [765bd0d5d4a0c852014c120c6930661d]
- R  D        [Cronbach Alpha] [1.1 AMSI : Cronba...] [2014-12-10 14:00:13] [765bd0d5d4a0c852014c120c6930661d]
- R  D        [Cronbach Alpha] [1.1 AMSI : Cronba...] [2014-12-10 14:01:50] [765bd0d5d4a0c852014c120c6930661d]
- R  D        [Cronbach Alpha] [1.1 AMSE : Cronba...] [2014-12-10 14:06:06] [765bd0d5d4a0c852014c120c6930661d]
- R  D        [Cronbach Alpha] [1.1 AMSE : Cronba...] [2014-12-10 14:08:25] [765bd0d5d4a0c852014c120c6930661d]
- R  D        [Cronbach Alpha] [1.1 AMSE : Cronba...] [2014-12-10 14:10:13] [765bd0d5d4a0c852014c120c6930661d]
-   PD      [Histogram] [1.1 AMSA : Histogram] [2014-12-10 14:13:39] [765bd0d5d4a0c852014c120c6930661d]
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Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
51
56
67
69
NA
56
55
NA
67
NA
NA
76
64
68
64
65
71
63
60
NA
72
70
61
61
62
71
NA
51
56
70
73
76
NA
NA
NA
52
NA
NA
NA
57
NA
60
60
NA
62
59
61
NA
NA
NA
NA
69
NA
59
NA
66
NA
67
NA
NA
75
NA
69
58
60
74
55
NA
63
NA
NA
NA
68
NA
62
NA
NA
NA
NA
72
62
75
58
NA
NA
47
NA
NA
NA
NA
19
50
NA
NA
79
NA
71
48
66
NA
74
66
71
NA
NA
NA
53
60
NA
70
69
NA
NA
NA
59
72
NA
NA
NA
71
74
NA
NA
NA
80
73
67
61
NA
74
32
69
NA
NA
64
NA
60
59
78
NA
60
NA
68
73
NA
67
NA
65
NA
74
NA
NA
55
49
NA
53
64
NA
57
NA
NA
67
70
NA
75
NA
NA
65
NA
NA
65
69
48
NA
68
74
67
65
NA
74
NA
NA
69
NA
63
NA
NA
68
NA
70
78
NA
NA
NA
74
NA
62
69
65
67
NA
52
NA
53
NA
NA
NA
NA
NA
NA
76
63
41
NA
NA
NA
NA
NA
72
52
65
63
NA
56
NA
56
64
NA
75
NA
NA
NA
NA
NA
NA
65
NA
NA
61
71
72
62
NA
66
63
NA
NA
NA
NA
71
NA
NA
NA
NA
NA
NA
64
78
60
NA
NA
68
NA
68
60
65
64
69
NA
NA
NA
NA
NA
74
NA
NA
76
NA
NA
73
NA
76
55
NA
62
NA
78
NA
67
75
59
NA
70
59
NA
63
67
58
71
NA
53
NA
NA
64
NA
67
72
NA
NA
57
62
74
54
NA
66
64
74
71
NA
NA
63
NA
70
66
NA
78
NA
72
NA
NA
72
58
84
67
NA
NA
63
NA
55
NA
58
69
54
58
67
77
80
67
NA
71
NA
NA
79
76
72
81
52
76
60
NA
77
64
67
NA
79
40
71
73
NA
70
66
NA
NA
74
58
51
75
NA
50
NA
77
NA
NA
NA
NA
71
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA

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=265078&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=265078&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265078&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
[10,20[1510.0025130.0025130.000469
[20,30[25000.0025130
[30,40[3510.0025130.0050250.000469
[40,50[4560.0150750.0201010.002817
[50,60[55410.1030150.1231160.019249
[60,70[65900.2261310.3492460.042254
[70,80[75700.1758790.5251260.032864
[80,90]8540.010050.5351760.001878

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[10,20[ & 15 & 1 & 0.002513 & 0.002513 & 0.000469 \tabularnewline
[20,30[ & 25 & 0 & 0 & 0.002513 & 0 \tabularnewline
[30,40[ & 35 & 1 & 0.002513 & 0.005025 & 0.000469 \tabularnewline
[40,50[ & 45 & 6 & 0.015075 & 0.020101 & 0.002817 \tabularnewline
[50,60[ & 55 & 41 & 0.103015 & 0.123116 & 0.019249 \tabularnewline
[60,70[ & 65 & 90 & 0.226131 & 0.349246 & 0.042254 \tabularnewline
[70,80[ & 75 & 70 & 0.175879 & 0.525126 & 0.032864 \tabularnewline
[80,90] & 85 & 4 & 0.01005 & 0.535176 & 0.001878 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265078&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][10,20[[/C][C]15[/C][C]1[/C][C]0.002513[/C][C]0.002513[/C][C]0.000469[/C][/ROW]
[ROW][C][20,30[[/C][C]25[/C][C]0[/C][C]0[/C][C]0.002513[/C][C]0[/C][/ROW]
[ROW][C][30,40[[/C][C]35[/C][C]1[/C][C]0.002513[/C][C]0.005025[/C][C]0.000469[/C][/ROW]
[ROW][C][40,50[[/C][C]45[/C][C]6[/C][C]0.015075[/C][C]0.020101[/C][C]0.002817[/C][/ROW]
[ROW][C][50,60[[/C][C]55[/C][C]41[/C][C]0.103015[/C][C]0.123116[/C][C]0.019249[/C][/ROW]
[ROW][C][60,70[[/C][C]65[/C][C]90[/C][C]0.226131[/C][C]0.349246[/C][C]0.042254[/C][/ROW]
[ROW][C][70,80[[/C][C]75[/C][C]70[/C][C]0.175879[/C][C]0.525126[/C][C]0.032864[/C][/ROW]
[ROW][C][80,90][/C][C]85[/C][C]4[/C][C]0.01005[/C][C]0.535176[/C][C]0.001878[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265078&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265078&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
[10,20[1510.0025130.0025130.000469
[20,30[25000.0025130
[30,40[3510.0025130.0050250.000469
[40,50[4560.0150750.0201010.002817
[50,60[55410.1030150.1231160.019249
[60,70[65900.2261310.3492460.042254
[70,80[75700.1758790.5251260.032864
[80,90]8540.010050.5351760.001878


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):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- ''
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')
}