Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSat, 03 Oct 2015 10:21:46 +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/2015/Oct/03/t1443864160mno02tvqx8rm5yu.htm/, Retrieved Wed, 15 May 2024 17:14:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=281226, Retrieved Wed, 15 May 2024 17:14:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2015-10-03 09:21:46] [047b71d569822bc9ea0d1a14ab5e311b] [Current]
- R  D    [Histogram] [] [2016-08-08 09:52:57] [39c526a439265efa15f7db403b90ebd6]
- R PD    [Histogram] [] [2016-08-08 10:20:07] [39c526a439265efa15f7db403b90ebd6]
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Dataseries X:
72.04
72.26
72.53
72.41
72.91
72.84
72.92
73.03
72.98
72.99
73.15
73.34
73.8
74.46
74.54
74.92
74.19
74.34
74.54
74.4
73.78
74.42
73.54
74.45
76.31
76.44
76.64
76.44
76.49
76.52
78.15
78.54
78.79
78.75
78.28
78.44
78.75
80.54
80.84
81.11
80.47
80.53
80.35
80.29
80.27
80.1
79.8
79.84
79.92
80.26
80.69
84.5
85.45
86.19
86.4
85.98
85.87
86.06
86.43
86.43
86.37
86.84
86.73
90.99
92.61
93.83
94.2
94.01
93.47
93.27
94.3
94.53
94.59
94.69
94.67
96.55
97.14
97.32
97.97
98.49
99.11
99.09
98.76
99.2
99.61
99.54
99.68
100.75
100.38
100.79
100.39
100.39
100.12
100
99.17
99.17
99.59
99.96
99.68
101.03
100.99
101.38
101.84
101.52
101.37
101.22
101.45
101.99




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281226&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281226&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281226&T=0

As an alternative you can also use a 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'Sir Maurice George Kendall' @ kendall.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[72,74[73150.1388890.1388890.069444
[74,76[7590.0833330.2222220.041667
[76,78[7760.0555560.2777780.027778
[78,80[79100.0925930.370370.046296
[80,82[81110.1018520.4722220.050926
[82,84[83000.4722220
[84,86[8540.0370370.5092590.018519
[86,88[8780.0740740.5833330.037037
[88,90[89000.5833330
[90,92[9110.0092590.5925930.00463
[92,94[9340.0370370.629630.018519
[94,96[9570.0648150.6944440.032407
[96,98[9740.0370370.7314810.018519
[98,100[99130.120370.8518520.060185
[100,102]101160.14814810.074074

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[72,74[ & 73 & 15 & 0.138889 & 0.138889 & 0.069444 \tabularnewline
[74,76[ & 75 & 9 & 0.083333 & 0.222222 & 0.041667 \tabularnewline
[76,78[ & 77 & 6 & 0.055556 & 0.277778 & 0.027778 \tabularnewline
[78,80[ & 79 & 10 & 0.092593 & 0.37037 & 0.046296 \tabularnewline
[80,82[ & 81 & 11 & 0.101852 & 0.472222 & 0.050926 \tabularnewline
[82,84[ & 83 & 0 & 0 & 0.472222 & 0 \tabularnewline
[84,86[ & 85 & 4 & 0.037037 & 0.509259 & 0.018519 \tabularnewline
[86,88[ & 87 & 8 & 0.074074 & 0.583333 & 0.037037 \tabularnewline
[88,90[ & 89 & 0 & 0 & 0.583333 & 0 \tabularnewline
[90,92[ & 91 & 1 & 0.009259 & 0.592593 & 0.00463 \tabularnewline
[92,94[ & 93 & 4 & 0.037037 & 0.62963 & 0.018519 \tabularnewline
[94,96[ & 95 & 7 & 0.064815 & 0.694444 & 0.032407 \tabularnewline
[96,98[ & 97 & 4 & 0.037037 & 0.731481 & 0.018519 \tabularnewline
[98,100[ & 99 & 13 & 0.12037 & 0.851852 & 0.060185 \tabularnewline
[100,102] & 101 & 16 & 0.148148 & 1 & 0.074074 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281226&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][72,74[[/C][C]73[/C][C]15[/C][C]0.138889[/C][C]0.138889[/C][C]0.069444[/C][/ROW]
[ROW][C][74,76[[/C][C]75[/C][C]9[/C][C]0.083333[/C][C]0.222222[/C][C]0.041667[/C][/ROW]
[ROW][C][76,78[[/C][C]77[/C][C]6[/C][C]0.055556[/C][C]0.277778[/C][C]0.027778[/C][/ROW]
[ROW][C][78,80[[/C][C]79[/C][C]10[/C][C]0.092593[/C][C]0.37037[/C][C]0.046296[/C][/ROW]
[ROW][C][80,82[[/C][C]81[/C][C]11[/C][C]0.101852[/C][C]0.472222[/C][C]0.050926[/C][/ROW]
[ROW][C][82,84[[/C][C]83[/C][C]0[/C][C]0[/C][C]0.472222[/C][C]0[/C][/ROW]
[ROW][C][84,86[[/C][C]85[/C][C]4[/C][C]0.037037[/C][C]0.509259[/C][C]0.018519[/C][/ROW]
[ROW][C][86,88[[/C][C]87[/C][C]8[/C][C]0.074074[/C][C]0.583333[/C][C]0.037037[/C][/ROW]
[ROW][C][88,90[[/C][C]89[/C][C]0[/C][C]0[/C][C]0.583333[/C][C]0[/C][/ROW]
[ROW][C][90,92[[/C][C]91[/C][C]1[/C][C]0.009259[/C][C]0.592593[/C][C]0.00463[/C][/ROW]
[ROW][C][92,94[[/C][C]93[/C][C]4[/C][C]0.037037[/C][C]0.62963[/C][C]0.018519[/C][/ROW]
[ROW][C][94,96[[/C][C]95[/C][C]7[/C][C]0.064815[/C][C]0.694444[/C][C]0.032407[/C][/ROW]
[ROW][C][96,98[[/C][C]97[/C][C]4[/C][C]0.037037[/C][C]0.731481[/C][C]0.018519[/C][/ROW]
[ROW][C][98,100[[/C][C]99[/C][C]13[/C][C]0.12037[/C][C]0.851852[/C][C]0.060185[/C][/ROW]
[ROW][C][100,102][/C][C]101[/C][C]16[/C][C]0.148148[/C][C]1[/C][C]0.074074[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281226&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281226&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[72,74[73150.1388890.1388890.069444
[74,76[7590.0833330.2222220.041667
[76,78[7760.0555560.2777780.027778
[78,80[79100.0925930.370370.046296
[80,82[81110.1018520.4722220.050926
[82,84[83000.4722220
[84,86[8540.0370370.5092590.018519
[86,88[8780.0740740.5833330.037037
[88,90[89000.5833330
[90,92[9110.0092590.5925930.00463
[92,94[9340.0370370.629630.018519
[94,96[9570.0648150.6944440.032407
[96,98[9740.0370370.7314810.018519
[98,100[99130.120370.8518520.060185
[100,102]101160.14814810.074074



Parameters (Session):
par1 = 12 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 12 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'TRUE'
par2 <- 'grey'
par1 <- '12'
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 {
barplot(mytab <- sort(table(x),T),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')
}