## Free Statistics

of Irreproducible Research!

Author's title
Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSun, 28 Feb 2010 09:49:46 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Feb/28/t1267375831e0goog3p2s38boz.htm/, Retrieved Thu, 30 May 2024 09:07:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=73611, Retrieved Thu, 30 May 2024 09:07:47 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact194
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Frequentietabel -...] [2010-02-22 15:46:48] [b99a9e8e0bee3918139b00a56dd346b9]
-   P     [Histogram] [Maximumprijs 2005] [2010-02-28 16:49:46] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-           [Histogram] [Maximumprijs 2005] [2010-02-28 17:04:29] [74be16979710d4c4e7c6647856088456]
-   P         [Histogram] [Maximumprijs 2005] [2010-02-28 17:06:04] [74be16979710d4c4e7c6647856088456]
-   P           [Histogram] [Maximumprijs 2005] [2010-02-28 17:10:48] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
20
25
15
15
25
25
25
21
30
25
20
40
13
30
25
20
25
20
25
20
20
15
15
12
20
5
20
15
25
22
20
22
25
20
20
35
30
25
20
20
20
25
25
15
20
35
25
25
30
23
10
22
25
25
22
30
20
25
25
22
25
25
25
22
25
12
18
20
20
22
30
25
22
20
50
30
25
20
30
22
25
30
22
25
22
22
25
25
25
20
22
15
20
30
20
25
30
35
22
12
30
15
10
30
9
25
20
20
35
25
35
30
12
25
15
25
25
20
20
6
15
40
20
40
25
25
20
15
15
22
24
22
20
25
25
25
35
40
20
22
22
20
25
25
18
25
20
25
30
20
22
35
22
25
25
25
25
22
23
35
15
25
18
22
25
25
28
30
20
25
25
30
22
30
10
10
25
20
22
25
25
15
22
25
25
28
22
30
25
20
25
25
20
30
20
30
50
19
20
28
20
25
35
25
25
15
16
20
20
25
30
20
25
25
25
20
20
25
25
30
22
20
25
25
18
18
20
25
25
30
25
20
25
20
20
20
22
18
22
20
15
25
25
20
25
15
22
25
25
15
12
25
30
22
15
22
25
12
18
30
25
25
40
24
25
15
25
20
25
25
25
20
30
20
25
30
22
25
25
25
50
19
50
25
35
20
20
20
20
20
25
25
25
20
20
20
20
25
18
25
22
22
30
30
8
20
25
30
50
22
20
10
25
25
25
25
18
25
20
25
30
18
20
25
22
22
20
20
25
20
20
20
20
25
20
10
20
25
30
25
50
30
30
50
15
25
25
22
20
22
30
25
18
22
22
30
40
25
20
10
20
9
15
20
15
20
30
12
15
12
20
15
12
25
20
25
25
25
30
20
25
15
15
22
10
15
10
20
25
20
20
38
20
20
20
40
25
25
30
25
10
20
25
12
15
25
20
22
22
20
25
25
25
15
40
20
20
16
25
15
20
25
20
30
50
20
25
20
30
30
25
25
12
25
25
25
20
20
20
15
20
25
15
25
50
30
20
20
25
12
15
20
20
35
22
15
18
30
22
12
12
20
20
15
25
15
20
20
25
18
30
20
25
25
25
20
20
25
20
22
15
15
22
20
10
25
20
20
15
12
20
5
20
15
15
25
25
25
15
25
22
25
20
18
22
25
35
25
25
25
35
30
22
30
50
15
25
24
20
25
25
25
12
15
22
25
25
25
25
15
20
20
15
35
30
20
22
65
20
25
22
20
25
25
20
25
15
20
12
15
10
25
15
30
35
25
25
25
25
25
40
40
25
25
20
25
25
22
25
30
25
25
30
25
25
30
25
25
20
22
22
20
25
22
25
22
40
25
25
25
22
20
35
20
35
25
22
25
25
25
25
25
40
25
30
25
20
25
25
30
22
22
20
15
15
25
25
20
20
15
25
15
20
22
25
15
15
18
5
15
25
18
40
25
25
20
30
20
25
25
25
22
22
25
25
30
25
25
25
25
20
20
25
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25
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20
30
25
22
30
20
20
30
25
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30
20
25
25
24
25
30
18
15
22
22
25
22
22
25
15
20
22
18
35
20
20
20
25
25
30
15
25
22
26
25
20
25
25
25
22
25
25
20
22
30
15
30
25
20
25
25
35
22
20
25
20
20
18
20
22
25
10
20
25
20
20
30
25
20
15
20
25
10
20
25
22
22
25
25
15
25
20
10
25
16
25
35
25
15
25
25
30
25
10
22
20
25
20
20
25
22
18
30
19
25
20
25
20
25
20
22
12
30
12
22
25
25
25
25
30
30
10
22
22
25
20
22
20
25
20
15
25
20
25
20
30
15
40
25
20
22
22
30
20
40
20
25
20
25
20
50
50
25
25
40
30
22
30
20
25
25
30
25
25
20
18
18
28
25
22
15
40
40
12
12
18
12
25
26
18
25
22
15
25
15
15
15
25
15
12
22
20
20
25
20
12
9
15
12
15
25
20
20
15
15
30
21
25
22
22
50
15
25
15
25
22
18
50
20
50
20
20
30
25
20
22
25
50
40
25
25
25
25
30
40
25
30
20

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=73611&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=73611&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=73611&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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135

 Frequency Table (Histogram) Bins Midpoint Abs. Frequency Rel. Frequency Cumul. Rel. Freq. Density [5,10[ 7.5 8 0.008889 0.008889 0.001778 [10,15[ 12.5 43 0.047778 0.056667 0.009556 [15,20[ 17.5 109 0.121111 0.177778 0.024222 [20,25[ 22.5 300 0.333333 0.511111 0.066667 [25,30[ 27.5 302 0.335556 0.846667 0.067111 [30,35[ 32.5 80 0.088889 0.935556 0.017778 [35,40[ 37.5 21 0.023333 0.958889 0.004667 [40,45[ 42.5 20 0.022222 0.981111 0.004444 [45,50[ 47.5 0 0 0.981111 0 [50,55[ 52.5 16 0.017778 0.998889 0.003556 [55,60[ 57.5 0 0 0.998889 0 [60,65] 62.5 1 0.001111 1 0.000222

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[5,10[ & 7.5 & 8 & 0.008889 & 0.008889 & 0.001778 \tabularnewline
[10,15[ & 12.5 & 43 & 0.047778 & 0.056667 & 0.009556 \tabularnewline
[15,20[ & 17.5 & 109 & 0.121111 & 0.177778 & 0.024222 \tabularnewline
[20,25[ & 22.5 & 300 & 0.333333 & 0.511111 & 0.066667 \tabularnewline
[25,30[ & 27.5 & 302 & 0.335556 & 0.846667 & 0.067111 \tabularnewline
[30,35[ & 32.5 & 80 & 0.088889 & 0.935556 & 0.017778 \tabularnewline
[35,40[ & 37.5 & 21 & 0.023333 & 0.958889 & 0.004667 \tabularnewline
[40,45[ & 42.5 & 20 & 0.022222 & 0.981111 & 0.004444 \tabularnewline
[45,50[ & 47.5 & 0 & 0 & 0.981111 & 0 \tabularnewline
[50,55[ & 52.5 & 16 & 0.017778 & 0.998889 & 0.003556 \tabularnewline
[55,60[ & 57.5 & 0 & 0 & 0.998889 & 0 \tabularnewline
[60,65] & 62.5 & 1 & 0.001111 & 1 & 0.000222 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=73611&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][5,10[[/C][C]7.5[/C][C]8[/C][C]0.008889[/C][C]0.008889[/C][C]0.001778[/C][/ROW]
[ROW][C][10,15[[/C][C]12.5[/C][C]43[/C][C]0.047778[/C][C]0.056667[/C][C]0.009556[/C][/ROW]
[ROW][C][15,20[[/C][C]17.5[/C][C]109[/C][C]0.121111[/C][C]0.177778[/C][C]0.024222[/C][/ROW]
[ROW][C][20,25[[/C][C]22.5[/C][C]300[/C][C]0.333333[/C][C]0.511111[/C][C]0.066667[/C][/ROW]
[ROW][C][25,30[[/C][C]27.5[/C][C]302[/C][C]0.335556[/C][C]0.846667[/C][C]0.067111[/C][/ROW]
[ROW][C][30,35[[/C][C]32.5[/C][C]80[/C][C]0.088889[/C][C]0.935556[/C][C]0.017778[/C][/ROW]
[ROW][C][35,40[[/C][C]37.5[/C][C]21[/C][C]0.023333[/C][C]0.958889[/C][C]0.004667[/C][/ROW]
[ROW][C][40,45[[/C][C]42.5[/C][C]20[/C][C]0.022222[/C][C]0.981111[/C][C]0.004444[/C][/ROW]
[ROW][C][45,50[[/C][C]47.5[/C][C]0[/C][C]0[/C][C]0.981111[/C][C]0[/C][/ROW]
[ROW][C][50,55[[/C][C]52.5[/C][C]16[/C][C]0.017778[/C][C]0.998889[/C][C]0.003556[/C][/ROW]
[ROW][C][55,60[[/C][C]57.5[/C][C]0[/C][C]0[/C][C]0.998889[/C][C]0[/C][/ROW]
[ROW][C][60,65][/C][C]62.5[/C][C]1[/C][C]0.001111[/C][C]1[/C][C]0.000222[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=73611&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=73611&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) Bins Midpoint Abs. Frequency Rel. Frequency Cumul. Rel. Freq. Density [5,10[ 7.5 8 0.008889 0.008889 0.001778 [10,15[ 12.5 43 0.047778 0.056667 0.009556 [15,20[ 17.5 109 0.121111 0.177778 0.024222 [20,25[ 22.5 300 0.333333 0.511111 0.066667 [25,30[ 27.5 302 0.335556 0.846667 0.067111 [30,35[ 32.5 80 0.088889 0.935556 0.017778 [35,40[ 37.5 21 0.023333 0.958889 0.004667 [40,45[ 42.5 20 0.022222 0.981111 0.004444 [45,50[ 47.5 0 0 0.981111 0 [50,55[ 52.5 16 0.017778 0.998889 0.003556 [55,60[ 57.5 0 0 0.998889 0 [60,65] 62.5 1 0.001111 1 0.000222

par1 <- as.numeric(par1)if (par3 == 'TRUE') par3 <- TRUEif (par3 == 'FALSE') par3 <- FALSEif (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.na(par1)) {myhist<-hist(x,col=par2,main=main,xlab=xlab,right=par3)} else {if (par1 < 0) par1 <- 3if (par1 > 50) par1 <- 50myhist<-hist(x,breaks=par1,col=par2,main=main,xlab=xlab,right=par3)}dev.off()myhistn <- 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 <- 0if (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='')elsedum <- paste(mybracket,myhist$breaks[i],sep='')dum <- paste(dum,myhist$breaks[i+1],sep=',')if (i==mynumrows)dum <- paste(dum,']',sep='')elsedum <- 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$counts[i]/ncrf <- crf + rfa<-table.element(a,round(rf,6))a<-table.element(a,round(crf,6))a<-table.element(a,round(myhist$density[i],6))a<-table.row.end(a)}a<-table.end(a)table.save(a,file='mytable.tab')