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Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationThu, 05 Mar 2009 07:28:29 -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/2009/Mar/05/t1236263362ykxdkf9jfxlsrhl.htm/, Retrieved Thu, 28 Mar 2024 20:23:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=38570, Retrieved Thu, 28 Mar 2024 20:23:51 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [] [2009-02-19 12:53:08] [6ba5e630245e7429afb91391e726fb00]
-       [Histogram] [Frequentietabel-s...] [2009-03-05 13:40:04] [74be16979710d4c4e7c6647856088456]
-           [Histogram] [Histogram-studio ...] [2009-03-05 14:28:29] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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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
25
25
25
20
30
25
22
30
20
20
30
25
25
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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=38570&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=38570&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38570&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'George Udny Yule' @ 72.249.76.132







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[5,10[7.580.0088890.0088890.001778
[10,15[12.5430.0477780.0566670.009556
[15,20[17.51090.1211110.1777780.024222
[20,25[22.53000.3333330.5111110.066667
[25,30[27.53020.3355560.8466670.067111
[30,35[32.5800.0888890.9355560.017778
[35,40[37.5210.0233330.9588890.004667
[40,45[42.5200.0222220.9811110.004444
[45,50[47.5000.9811110
[50,55[52.5160.0177780.9988890.003556
[55,60[57.5000.9988890
[60,65]62.510.00111110.000222

\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=38570&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=38570&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38570&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
[5,10[7.580.0088890.0088890.001778
[10,15[12.5430.0477780.0566670.009556
[15,20[17.51090.1211110.1777780.024222
[20,25[22.53000.3333330.5111110.066667
[25,30[27.53020.3355560.8466670.067111
[30,35[32.5800.0888890.9355560.017778
[35,40[37.5210.0233330.9588890.004667
[40,45[42.5200.0222220.9811110.004444
[45,50[47.5000.9811110
[50,55[52.5160.0177780.9988890.003556
[55,60[57.5000.9988890
[60,65]62.510.00111110.000222



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.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)
}
dev.off()
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')