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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationWed, 01 Oct 2014 15:21:46 +0100
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/Oct/01/t1412173437qo3bn1ernn2r0m5.htm/, Retrieved Sun, 12 May 2024 15:10:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=237550, Retrieved Sun, 12 May 2024 15:10:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Werkloze beroepsb...] [2014-09-18 13:15:26] [be6f075fcfffb6e204f178c2e69229d5]
- R     [Histogram] [Werkloze beroepsb...] [2014-09-26 14:06:07] [be6f075fcfffb6e204f178c2e69229d5]
-   P     [Histogram] [Werkloze beroepsb...] [2014-09-26 14:10:00] [be6f075fcfffb6e204f178c2e69229d5]
-   P       [Histogram] [Werkloze beroepsb...] [2014-09-26 14:14:11] [be6f075fcfffb6e204f178c2e69229d5]
-    D          [Histogram] [Werkloze beroepsb...] [2014-10-01 14:21:46] [30b408b6447afc100cbee3b5fe745b69] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
82
80
76
73
70
68
67
64
69
69
67
57
67
69
67
66
65
56
57
53
58
59
60
59
65
62
61
62
57
51
45
46
48
49
48
43
51
54
57
60
58
61
62
62
64
68
70
73
79
84
82
78
78
76
73
71
71
70
74
72
80
80
80
79
82
71
75
74
76
82
85
82
92
93
93
99
98
89
96
94
99
108
113
115
126
131
134
134
137
139
139
134
133
135
130
133

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 0 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=237550&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=237550&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=237550&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 time0 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[40,45[42.510.0104170.0104170.002083
[45,50[47.550.0520830.06250.010417
[50,55[52.540.0416670.1041670.008333
[55,60[57.590.093750.1979170.01875
[60,65[62.5100.1041670.3020830.020833
[65,70[67.5120.1250.4270830.025
[70,75[72.5120.1250.5520830.025
[75,80[77.580.0833330.6354170.016667
[80,85[82.5100.1041670.7395830.020833
[85,90[87.520.0208330.7604170.004167
[90,95[92.540.0416670.8020830.008333
[95,100[97.540.0416670.843750.008333
[100,105[102.5000.843750
[105,110[107.510.0104170.8541670.002083
[110,115[112.510.0104170.8645830.002083
[115,120[117.510.0104170.8750.002083
[120,125[122.5000.8750
[125,130[127.510.0104170.8854170.002083
[130,135[132.570.0729170.9583330.014583
[135,140]137.540.04166710.008333

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[40,45[ & 42.5 & 1 & 0.010417 & 0.010417 & 0.002083 \tabularnewline
[45,50[ & 47.5 & 5 & 0.052083 & 0.0625 & 0.010417 \tabularnewline
[50,55[ & 52.5 & 4 & 0.041667 & 0.104167 & 0.008333 \tabularnewline
[55,60[ & 57.5 & 9 & 0.09375 & 0.197917 & 0.01875 \tabularnewline
[60,65[ & 62.5 & 10 & 0.104167 & 0.302083 & 0.020833 \tabularnewline
[65,70[ & 67.5 & 12 & 0.125 & 0.427083 & 0.025 \tabularnewline
[70,75[ & 72.5 & 12 & 0.125 & 0.552083 & 0.025 \tabularnewline
[75,80[ & 77.5 & 8 & 0.083333 & 0.635417 & 0.016667 \tabularnewline
[80,85[ & 82.5 & 10 & 0.104167 & 0.739583 & 0.020833 \tabularnewline
[85,90[ & 87.5 & 2 & 0.020833 & 0.760417 & 0.004167 \tabularnewline
[90,95[ & 92.5 & 4 & 0.041667 & 0.802083 & 0.008333 \tabularnewline
[95,100[ & 97.5 & 4 & 0.041667 & 0.84375 & 0.008333 \tabularnewline
[100,105[ & 102.5 & 0 & 0 & 0.84375 & 0 \tabularnewline
[105,110[ & 107.5 & 1 & 0.010417 & 0.854167 & 0.002083 \tabularnewline
[110,115[ & 112.5 & 1 & 0.010417 & 0.864583 & 0.002083 \tabularnewline
[115,120[ & 117.5 & 1 & 0.010417 & 0.875 & 0.002083 \tabularnewline
[120,125[ & 122.5 & 0 & 0 & 0.875 & 0 \tabularnewline
[125,130[ & 127.5 & 1 & 0.010417 & 0.885417 & 0.002083 \tabularnewline
[130,135[ & 132.5 & 7 & 0.072917 & 0.958333 & 0.014583 \tabularnewline
[135,140] & 137.5 & 4 & 0.041667 & 1 & 0.008333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=237550&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][40,45[[/C][C]42.5[/C][C]1[/C][C]0.010417[/C][C]0.010417[/C][C]0.002083[/C][/ROW]
[ROW][C][45,50[[/C][C]47.5[/C][C]5[/C][C]0.052083[/C][C]0.0625[/C][C]0.010417[/C][/ROW]
[ROW][C][50,55[[/C][C]52.5[/C][C]4[/C][C]0.041667[/C][C]0.104167[/C][C]0.008333[/C][/ROW]
[ROW][C][55,60[[/C][C]57.5[/C][C]9[/C][C]0.09375[/C][C]0.197917[/C][C]0.01875[/C][/ROW]
[ROW][C][60,65[[/C][C]62.5[/C][C]10[/C][C]0.104167[/C][C]0.302083[/C][C]0.020833[/C][/ROW]
[ROW][C][65,70[[/C][C]67.5[/C][C]12[/C][C]0.125[/C][C]0.427083[/C][C]0.025[/C][/ROW]
[ROW][C][70,75[[/C][C]72.5[/C][C]12[/C][C]0.125[/C][C]0.552083[/C][C]0.025[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]8[/C][C]0.083333[/C][C]0.635417[/C][C]0.016667[/C][/ROW]
[ROW][C][80,85[[/C][C]82.5[/C][C]10[/C][C]0.104167[/C][C]0.739583[/C][C]0.020833[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]2[/C][C]0.020833[/C][C]0.760417[/C][C]0.004167[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]4[/C][C]0.041667[/C][C]0.802083[/C][C]0.008333[/C][/ROW]
[ROW][C][95,100[[/C][C]97.5[/C][C]4[/C][C]0.041667[/C][C]0.84375[/C][C]0.008333[/C][/ROW]
[ROW][C][100,105[[/C][C]102.5[/C][C]0[/C][C]0[/C][C]0.84375[/C][C]0[/C][/ROW]
[ROW][C][105,110[[/C][C]107.5[/C][C]1[/C][C]0.010417[/C][C]0.854167[/C][C]0.002083[/C][/ROW]
[ROW][C][110,115[[/C][C]112.5[/C][C]1[/C][C]0.010417[/C][C]0.864583[/C][C]0.002083[/C][/ROW]
[ROW][C][115,120[[/C][C]117.5[/C][C]1[/C][C]0.010417[/C][C]0.875[/C][C]0.002083[/C][/ROW]
[ROW][C][120,125[[/C][C]122.5[/C][C]0[/C][C]0[/C][C]0.875[/C][C]0[/C][/ROW]
[ROW][C][125,130[[/C][C]127.5[/C][C]1[/C][C]0.010417[/C][C]0.885417[/C][C]0.002083[/C][/ROW]
[ROW][C][130,135[[/C][C]132.5[/C][C]7[/C][C]0.072917[/C][C]0.958333[/C][C]0.014583[/C][/ROW]
[ROW][C][135,140][/C][C]137.5[/C][C]4[/C][C]0.041667[/C][C]1[/C][C]0.008333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=237550&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=237550&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
[40,45[42.510.0104170.0104170.002083
[45,50[47.550.0520830.06250.010417
[50,55[52.540.0416670.1041670.008333
[55,60[57.590.093750.1979170.01875
[60,65[62.5100.1041670.3020830.020833
[65,70[67.5120.1250.4270830.025
[70,75[72.5120.1250.5520830.025
[75,80[77.580.0833330.6354170.016667
[80,85[82.5100.1041670.7395830.020833
[85,90[87.520.0208330.7604170.004167
[90,95[92.540.0416670.8020830.008333
[95,100[97.540.0416670.843750.008333
[100,105[102.5000.843750
[105,110[107.510.0104170.8541670.002083
[110,115[112.510.0104170.8645830.002083
[115,120[117.510.0104170.8750.002083
[120,125[122.5000.8750
[125,130[127.510.0104170.8854170.002083
[130,135[132.570.0729170.9583330.014583
[135,140]137.540.04166710.008333


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 16 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 16 ; 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')
}