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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationThu, 13 Dec 2012 10:51:10 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/13/t13554138855hgud4luqgow6du.htm/, Retrieved Sun, 28 Apr 2024 21:27:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=199294, Retrieved Sun, 28 Apr 2024 21:27:29 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Pearson Correlation] [Connected vs Sepa...] [2010-10-04 07:35:56] [b98453cac15ba1066b407e146608df68]
- RMPD    [Histogram] [Normaalverdeling] [2012-12-13 15:51:10] [4a7f0d88a508b07834eb6aeade20035b] [Current]
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Dataseries X:
34
33
29
34
32
35
41
27
40
40
36
40
43
40
33
37
32
26
36
39
38
34
35
41
42
36
39
33
33
36
37
36
34
32
35
39
30
25
29
39
31
26
28
40
32
35
32
41
34
36
38
34
32
34
32
40
43
35
45
36
39
31
36
36
37
40
35
36
32
36
37
42
37
36
36
33
37
35
37
28
33
45
38
43
37
36
40
39
43
32
37
34
44
35
34
37
40
36
44
35
34
40
34
39
36
40
37
35
45
39
39
37
38
46
37
27
33
42
33
33
33
38
37
35
33
39
38
39
38
30
43
34
39
36
32
37
42
40
35
39
34
28
30
36
31
34
33
37
40
39
42
47
38
38
40
37
29
37
37
33
31
36
37
39
35
33
37
42
31
32
36
32
40
32
30
37
42
37
47
37
31
41
44
40
37
33
35
40
38
36
36
35
30
37
43
33
39
38
40
29
35
37
26
28
38
29
35
38
39
44
33
35
42
30
36
40
39
36
37
37
37
36
30
32
35
42
41
35
33
39
34
39
41
34
30
29
33
40
32
37
37
36
41
34
38
40
42
32
40
38
35
34
38
24
39
42
44
35
37
34
41
33
42
30
30
40
49
39
29
39
35
35
34
24
47
24
30
34
41
32
32
35
37
40
45
35
39
46
33
40
35
38
36
34
30
44
37
36
37
34
43
31
34
38
38
34
26
36
35
37
40
43
29
30
36
38
43
41
31
36
44
35
42
31
38
34
40
41
30
43




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199294&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199294&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199294&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'Gertrude Mary Cox' @ cox.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[24,26[2540.0121210.0121210.006061
[26,28[2760.0181820.0303030.009091
[28,30[29120.0363640.0666670.018182
[30,32[31230.0696970.1363640.034848
[32,34[33390.1181820.2545450.059091
[34,36[35550.1666670.4212120.083333
[36,38[37680.2060610.6272730.10303
[38,40[39450.1363640.7636360.068182
[40,42[41380.1151520.8787880.057576
[42,44[43230.0696970.9484850.034848
[44,46[45110.0333330.9818180.016667
[46,48[4750.0151520.996970.007576
[48,50]4910.0030310.001515

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[24,26[ & 25 & 4 & 0.012121 & 0.012121 & 0.006061 \tabularnewline
[26,28[ & 27 & 6 & 0.018182 & 0.030303 & 0.009091 \tabularnewline
[28,30[ & 29 & 12 & 0.036364 & 0.066667 & 0.018182 \tabularnewline
[30,32[ & 31 & 23 & 0.069697 & 0.136364 & 0.034848 \tabularnewline
[32,34[ & 33 & 39 & 0.118182 & 0.254545 & 0.059091 \tabularnewline
[34,36[ & 35 & 55 & 0.166667 & 0.421212 & 0.083333 \tabularnewline
[36,38[ & 37 & 68 & 0.206061 & 0.627273 & 0.10303 \tabularnewline
[38,40[ & 39 & 45 & 0.136364 & 0.763636 & 0.068182 \tabularnewline
[40,42[ & 41 & 38 & 0.115152 & 0.878788 & 0.057576 \tabularnewline
[42,44[ & 43 & 23 & 0.069697 & 0.948485 & 0.034848 \tabularnewline
[44,46[ & 45 & 11 & 0.033333 & 0.981818 & 0.016667 \tabularnewline
[46,48[ & 47 & 5 & 0.015152 & 0.99697 & 0.007576 \tabularnewline
[48,50] & 49 & 1 & 0.00303 & 1 & 0.001515 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199294&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][24,26[[/C][C]25[/C][C]4[/C][C]0.012121[/C][C]0.012121[/C][C]0.006061[/C][/ROW]
[ROW][C][26,28[[/C][C]27[/C][C]6[/C][C]0.018182[/C][C]0.030303[/C][C]0.009091[/C][/ROW]
[ROW][C][28,30[[/C][C]29[/C][C]12[/C][C]0.036364[/C][C]0.066667[/C][C]0.018182[/C][/ROW]
[ROW][C][30,32[[/C][C]31[/C][C]23[/C][C]0.069697[/C][C]0.136364[/C][C]0.034848[/C][/ROW]
[ROW][C][32,34[[/C][C]33[/C][C]39[/C][C]0.118182[/C][C]0.254545[/C][C]0.059091[/C][/ROW]
[ROW][C][34,36[[/C][C]35[/C][C]55[/C][C]0.166667[/C][C]0.421212[/C][C]0.083333[/C][/ROW]
[ROW][C][36,38[[/C][C]37[/C][C]68[/C][C]0.206061[/C][C]0.627273[/C][C]0.10303[/C][/ROW]
[ROW][C][38,40[[/C][C]39[/C][C]45[/C][C]0.136364[/C][C]0.763636[/C][C]0.068182[/C][/ROW]
[ROW][C][40,42[[/C][C]41[/C][C]38[/C][C]0.115152[/C][C]0.878788[/C][C]0.057576[/C][/ROW]
[ROW][C][42,44[[/C][C]43[/C][C]23[/C][C]0.069697[/C][C]0.948485[/C][C]0.034848[/C][/ROW]
[ROW][C][44,46[[/C][C]45[/C][C]11[/C][C]0.033333[/C][C]0.981818[/C][C]0.016667[/C][/ROW]
[ROW][C][46,48[[/C][C]47[/C][C]5[/C][C]0.015152[/C][C]0.99697[/C][C]0.007576[/C][/ROW]
[ROW][C][48,50][/C][C]49[/C][C]1[/C][C]0.00303[/C][C]1[/C][C]0.001515[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199294&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199294&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
[24,26[2540.0121210.0121210.006061
[26,28[2760.0181820.0303030.009091
[28,30[29120.0363640.0666670.018182
[30,32[31230.0696970.1363640.034848
[32,34[33390.1181820.2545450.059091
[34,36[35550.1666670.4212120.083333
[36,38[37680.2060610.6272730.10303
[38,40[39450.1363640.7636360.068182
[40,42[41380.1151520.8787880.057576
[42,44[43230.0696970.9484850.034848
[44,46[45110.0333330.9818180.016667
[46,48[4750.0151520.996970.007576
[48,50]4910.0030310.001515



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.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')
}